Chapter 11: Department of Electrical and Computer Engineering

Professors Emeritus: Timothy J. Healy, Dragoslav D. Siljak, Sarah Kate Wilson
Thomas J. Bannan Professor: Shoba Krishnan (Department Chair)
Professors: Tokunbo Ogunfunmi, Sally L. Wood, Cary Y. Yang, Aleksandar Zecevic
Associate Professors: Maryam Khanbaghi, M. Mahmudur Rahman, Kurt Schab, Hoeseok Yang
Assistant Professors: Anoosheh Heidarzadeh, Maria Kyrarini, Dat Tran, S.J.

Overview

The field of electrical and computer engineering covers the design, construction, testing, and operation of electrical components, circuits, and systems. Electrical and computer engineers work with information representation, processing and transmission; advancing integrated circuit design for digital, analog, and mixed signals systems; designing and characterizing antennas, RF, microwave and millimeter-wave Systems; new devices and architectures, energy systems and renewable energy; nanotechnology; and all the areas of information circuits and systems that have traditionally supported these efforts. This includes all phases of the digital or analog transmission of information, such as in mobile communications and networks, radio, television, telephone systems, fiber optics, and satellite communications, as well as control and robotics, electric power, information processing and storage.

The Electrical and Computer Engineering Programs are supported by the facilities of the University’s Academic Computing Center, as well as by the Engineering Computing Center. The department supports 10 major teaching and research laboratories, five additional laboratories used only for teaching, and a laboratory dedicated to the support of design projects. The five teaching laboratories cover the fields of digital systems, electric circuits, electronics, systems, and RF and communication and signal processing and control systems, logic design and digital systems, In addition, the program has a laboratory dedicated to senior design projects.

Programs are offered which lead to a Master’s Degree, a Ph.D. degree, an Engineer’s Degree, or a Certificate. Each is described below.

Master’s Degree Program

The master’s degree will be granted to degree candidates who complete a program of studies approved by a faculty advisor. The program must consist of no less than 46 units, and a 3.000 cumulative GPA (B average) must be earned in all coursework taken at Santa Clara University. Residence requirements are met by completing no less than 37 units of the graduate program at Santa Clara University. A maximum of nine quarter units (six-semester units) of graduate-level coursework may be transferred from other accredited institutions at the discretion of the student’s advisor. All units applied toward the degree, including those transferred from other institutions, must be earned within six years from initial enrollment. The program may include a thesis or a research component of smaller scope that does not require a thesis.

The program requires that students select one of these defined focus areas within electrical and computer engineering.

Power Systems and Control

Autonomous cars, space shuttles, robots, IoT and airplanes all have sophisticated control strategies. The electric utility industry is probably the largest and most complex industry in the world. How this network operates, and how it can be controlled, and how to integrate renewable energies into the grid in order to have cleaner and more sustainable energy are major challenges. 

Faculty Advisors: Maryam Khanbaghi, Aleksandar Zecevic

IC Design and Technology

The study of integrated circuits (IC) (generally known as semiconductors or chips) consists of three interconnected areas of pedagogy, Circuit Design, Device Physics, and Fabrication Process Technology. One cannot imagine the world now and in the future without chips, which are in your home, in your workplace, in your automobile, and in all your electronic devices. With worldwide chips revenue projected to approach $1 trillion by 2030, the semiconductor industry, not unlike its energy counterpart, supplies the critical goods and services that sustain and advance human civilization.

Faculty Advisors: Shoba Krishnan, Cary Yang, Mahmudur Rahman

RF and Applied Electromagnetics

From 5G and the internet of things to automotive radar, high frequency and wireless systems are pervasive in nearly every aspect of modern technology. To prepare engineers for careers in these contemporary fields, the RF and Applied Electromagnetics program provides the fundamental theoretical and applied knowledge for design, analysis, and implementation of high frequency circuits and systems.

Faculty Advisor: Kurt Schab

Signal Processing and Machine Learning

Signal processing algorithms, architectures, and systems are at the heart of modern technologies that generate, transform, and interpret information across applications as diverse as communications, robotics and autonomous navigation, biotechnology and entertainment. This focus area includes courses in theory, architectures, implementations, and specific applications including computer vision and speech processing.

Faculty Advisors: Maria Kyrarini, Tokunbo Ogunfunmi, Sally Wood

Digital Systems

Digital systems include the three broad areas of computer architecture, digital design principles, techniques and verification, and embedded systems. Systems that execute software, whether they be general-purpose computers or computing platforms (digital platforms) embedded into a targeted application, fall into the category of digital systems, as do special purpose hardware implementations that might be realized with an FPGA or manufactured as an ASIC.

Faculty Advisors: Hoeseok Yang

Communication Systems and Information Theory

Information systems are vital to modern technology, driving a broad spectrum of applications from wireless networks and internet security to machine learning and AI. Our Communication Systems and Information Theory program prepares engineers for impactful careers in these rapidly evolving fields. The program offers both theoretical foundations and practical applications of storage, networking, and computing systems to meet the dynamic demands of security, privacy, and reliability in today's interconnected world.

Faculty Advisor: Anoosheh Heidarzadeh

Master Degree Requirements

Students must develop a program of studies with an academic advisor and file the approved program during their first term of enrollment at Santa Clara University. The program of studies must contain a minimum of 46 units of graduate-level engineering courses which include at least 27 units of courses offered within the electrical and computer department and no more than four units of engineering management courses.

The Master’s degree program of studies must include the following:

Graduate Core (minimum 4 units): Students must take a minimum of 4 units of the Graduate Core

  • One course must be from the “Engineering and Society” area.
  • One course must be selected from the “Professional Development” area.  
  • For additional information please see Chapter 6 which includes lists of courses which can satisfy the area requirements.

Applied Mathematics (4 units)

Electrical and Computer Engineering primary focus area (minimum 6 units). Students must select and meet the requirements of one of the six focus areas listed below:

  • Power Systems and Control Either (236 or 281A) and two courses selected from (211, 232, 281B, 333)
  • IC Design and Technology Three courses selected from (252, 261, 270, 387)
  • RF and Applied Electromagnetics 201 and two courses selected from (202, 203, 204, 624, 701, 706)
  • Signal Processing and Machine Learning 233 and two courses selected from (234, 421, 431, 520, 640, 644)
  • Digital Systems 501, 511, and 603
  • Communications 241 and 243, and one course selected from (244, 444, 446)

Electrical and Computer Engineering breadth: (minimum 4 units)

Two other focus areas must be selected as breadth areas. For each breadth area, one course must be taken from the list of required courses for that area.

Additional graduate courses recommended and approved by the graduate program advisor. This may include up to 6 units of Directed Research (299) and up to 9 units of Master’s Thesis Research (297). More detailed information about the Master’s Thesis can be found below.

These M.S. degree requirements may be adjusted by the advisor based on the student’s previous graduate work.

An advisor may approve selected undergraduate classes that do not duplicate course content of graduate courses in the program of studies. No more than 15 units of electives may be selected from the following upper-division undergraduate courses: 105, 112, 116, 117, 118, 130, 133, 141, 144, 151, 152, 156, 160, 164, 183 and 184.

Alterations in the approved program, consistent with the above departmental requirements, may be requested at any time by a petition initiated by the student and approved by the advisor.

Students with relevant technical backgrounds may be admitted to the master’s program without an undergraduate degree in electrical or electrical and computer engineering from an accredited program. In order to guarantee prerequisites for graduate courses, those students must take sufficient additional courses beyond the 46-unit minimum to ensure coverage of all areas of the undergraduate EE or ECE core requirements. A student who has earned a Fundamentals of Electrical and Computer Engineering Certificate will have satisfied these background requirements.

The advisor will determine which courses must be taken to meet these requirements. Undergraduate core courses will not be included in the 46 units required for the master’s degree.

Please Note: In general, no credit will be allowed for courses that duplicate prior coursework, including courses listed above as degree requirements. (However, graduate-level treatment of a topic is more advanced than an undergraduate course with a similar title.) Students should discuss any adjustments of these requirements with their academic advisor before filing their program of studies. In all cases, prerequisite requirements should be interpreted to mean the course specified or an equivalent course taken elsewhere.

Master’s Thesis Research

Master’s thesis research consists of a minimum of 7 units and a maximum of 15 units, which are included in “Additional Elective Courses” in the Master’s Program of Study. The first stage of the research is 6 units of Directed Research, ECEN 299. Students with an average grade of B+ or higher may continue to stage 2, which is advanced research and thesis composition. This stage requires 1 to 9 units of ECEN 297 and the submission of the completed thesis to the University library.

Ph.D. Program and Requirements

The Doctor of Philosophy (Ph.D.) degree is conferred by the School of Engineering primarily in recognition of competence in the subject field and the ability to investigate engineering problems independently, resulting in a new contribution to knowledge in the field. The work for the degree consists of engineering research, the preparation of a thesis based on that research, publication of the research, and a program of advanced studies in engineering, mathematics, and related physical sciences.

Preliminary Examination

The preliminary examination shall be written and shall include subject matter deemed by the major department to represent sufficient preparation in depth and breadth for advanced study in the major. Only those who pass the written examination may proceed to the subsequent Research Aptitude and Comprehensive examination.

Students currently studying at Santa Clara University for a master’s degree who are accepted for the Ph.D. program and who are at an advanced stage of the M.S. program may, with the approval of their academic advisor, take the preliminary examination before completing the M.S. degree requirements. Students who have completed the M.S. degree requirements and have been accepted for the Ph.D. program should take the preliminary examination as soon as possible but not more than two years after beginning the program.

Only those students who pass the preliminary examination shall be allowed to continue in the doctoral program. The preliminary examination may be repeated only once, and then only at the discretion of the thesis advisor.

Research Aptitude Examination (RAE)

The doctoral research aptitude milestone is the second major milestone in the progression towards a Ph.D. degree. This exam is designed to foster and evaluate the student’s breadth of knowledge based on their performance in graduate level coursework and growing knowledge in their specific topic of interest. It also tests the student’s suitability for conducting competent research, which includes evaluating their technical writing and presentation skills.

General Requirements

Doctoral Advisor

It is the student’s responsibility to obtain consent from a full-time faculty member in the student’s major department to serve as his/her prospective doctoral advisor. It is strongly recommended that Ph.D. students find a doctoral advisor before taking the preliminary examination. After passing the preliminary examination, Ph.D. students must have an advisor before the beginning of the next quarter following the preliminary examination. Students currently pursuing a master’s degree at the time of their preliminary examination should have a doctoral advisor as soon as possible after being accepted as a Ph.D. student.

The student and the advisor jointly develop a complete program of studies for research in a particular area. The complete program of studies (and any subsequent changes) must be filed with the Graduate Programs Office and approved by the student’s doctoral committee. Until this approval is obtained, there is no guarantee that courses taken will be acceptable toward the Ph.D. course requirements.

Doctoral Committee

After passing the Ph.D. preliminary exam, a student requests their advisor to form a doctoral committee. The committee consists of at least five members, each of whom must have earned a doctoral degree in a field of engineering or a related discipline. This includes the student’s doctoral advisor, at least two other current faculty members of the student’s major department at Santa Clara University, and at least one current faculty member from another appropriate academic department at Santa Clara University. The committee reviews the student’s program of study, conducts an oral comprehensive exam, conducts the dissertation defense, approves the required publication, and reviews the dissertation. Successful completion of the doctoral program requires that the student’s program of study, performance on the oral comprehensive examination, dissertation defense, and dissertation meet with the approval of all committee members.

Residence

The doctoral degree is granted based on achievement, rather than on the accumulation of units of credit. However, the candidate is expected to complete a minimum of 72 quarter units of graduate credit beyond the master’s degree. Of these, 36 quarter units may be earned through coursework and independent study, and 36 through doctoral research units. All Ph.D. research units are graded on a Pass/No Pass basis. A maximum of 18 quarter units (12-semester units) may be transferred from other accredited institutions at the discretion of the student’s advisor.

Ph.D. students must undertake a minimum of four consecutive quarters of full-time study at the University; spring and fall quarters are considered consecutive. The residency time shall normally be any period between passing the preliminary examination and completion of the thesis. For this requirement, full-time study is interpreted as a minimum registration of eight units per quarter during the academic year and four units during the summer session. Any variation from this requirement must be approved by the doctoral committee.

Comprehensive Examinations and Admission to Candidacy

After completion of the formal coursework approved by the doctoral committee, the student shall present their research proposal as part of a comprehensive oral examination on the coursework and the subject of their research work. This represents the third major milestone in the Ph.D. program. The student should make arrangements for the comprehensive examinations through the doctoral committee. A student who passes the comprehensive examinations is considered a degree candidate. The comprehensive examinations typically must be completed within four years from the time the student is admitted to the doctoral program. Comprehensive examinations may be repeated once, in whole or in part, at the discretion of the doctoral committee.

Doctoral Research and Dissertation Defense

The period following the comprehensive examinations is devoted to research, although such research may begin before the examinations are complete. After successfully completing the comprehensive examinations, the student must pass an oral examination on their research and dissertation, conducted by the doctoral committee and whomever they appoint as examiners. The dissertation must be made available to all examiners one month prior to the examination. The oral examination shall consist of a presentation of the research results and the defense. This examination is open to the public, but only members of the doctoral committee have a vote.

Dissertation and Publication

At least one month before the degree is to be conferred, the candidate must submit one copy of the final version of the dissertation to the department. The dissertation will not be considered as accepted until a copy signed by all committee members has been submitted to the library and one or more refereed articles based on it are accepted for publication in a first-tier professional or scientific journal approved by the doctoral committee. The final version of the dissertation must be filed with the library

Time Limit for Completing Degree

All requirements for the doctoral degree must be completed within eight years following initial enrollment in the Ph.D. program. This includes any leave of absences/withdrawals. Extensions will be allowed only in unusual circumstances and must be recommended in writing by the student’s doctoral committee and approved by the dean of engineering in consultation with the Graduate Program Leadership Council.

Additional Graduation Requirements

The requirements for the doctoral degree in the School of Engineering have been made to establish the structure in which the degree may be earned. Upon written approval of the provost, the dean of the School of Engineering, the doctoral committee, and the chair of the major department, other degree requirements may be established. The University reserves the right to evaluate the undertakings and the accomplishments of the degree candidate in total, and award or withhold the degree as a result of its deliberations. 

Engineer’s Degree Program and Requirements

The program leading to the Engineer’s Degree is particularly designed for the education of the practicing engineer. The degree is granted on completion of an approved academic program and a record of acceptable technical achievement in the candidate’s field of engineering. The academic program consists of a minimum of 46 quarter units beyond the master’s degree. Courses are selected to advance competence in specific areas relating to the engineering professional’s work. Evidence of technical achievement must include a paper principally written by the candidate and accepted for publication by a recognized engineering journal prior to the granting of the degree. A letter from the journal accepting the paper must be submitted to the department chair. In certain cases, the department may accept publication in the peer-reviewed proceedings of an appropriate national or international conference.

Electrical and Computer Engineering courses at the introductory Master of Science level (e.g., ECEN 210, 211, 212, 230, 231, 236, 241, 250, 261; and AMTH 210, 211, 220, 221, 230, 231, 235, 236, 240, 245, 246) are not generally acceptable in an Engineer’s Degree program of studies. However, with the approval of the advisor, the student may include up to three of these courses in the Engineer’s Degree program. The department also requires that at least 15 units of the program of studies be in topics other than the student’s major field of concentration. Candidates admitted to the Electrical and Computer Engineering Program who have M.S. degrees in fields other than electrical and computer engineering must include in their graduate programs (M.S. and Engineer’s Degree combined) a total of at least 46 units of graduate-level electrical and computer engineering coursework approved by an academic advisor.

Certificate Programs

General Information

Certificate programs are designed to provide an intensive background in a narrow area at the graduate level. At roughly one-third of the units of a master’s degree program, the certificate is designed to be completed in a much shorter period of time. These certificate programs are appropriate for students working in the industry who wish to update their skills or those interested in changing their career path. Students can only take courses that are required for the certificate.

Admission

To be accepted into a certificate program, the applicant must have a bachelor’s degree and meet any additional requirements for the specific certificate. Exceptions based on work experience may be granted for the Certificate in Fundamentals of Electrical and Computer Engineering. Admitted students are responsible for ensuring that they have the prerequisites for all courses they take in the Certificate Program.

Grade Requirements

Students must receive a minimum grade of C in each course and have an overall GPA of 3.000 or better to earn a certificate.

Continuation for a Master’s Degree

All Santa Clara University graduate courses applied to the completion of a certificate program earn graduate credit that may also be applied toward a graduate degree. Students who wish to continue for such a degree must submit a separate application and satisfy all normal admission requirements. The general GRE test requirement for graduate admission to the master’s degree will be waived for students who complete a certificate program with a GPA of 3.500 or higher.

Academic Requirements

Individual certificates are described briefly below. Additional information can be found in Chapter 17.

Digital System Design
Advisor: Dr. Hoeseok Yang

This certificate program has a triple purpose: (a) to increase design skills in digital system development, (b) to strengthen fundamental knowledge of computer architecture, digital design and embedded systems; and (c) to introduce the digital system designer to state-of-the-art tools and techniques. The program consists of the courses listed below totaling 16 units. Any change in the requirements must be approved by the academic advisor.

Integrated Circuit Design and Technology
Advisors:
Dr. Shoba Krishnan, Dr. Cary Yang, Dr. Mahmudur Rahman

The study of integrated circuits consists of three interconnected areas: Design, Devices and Process Technology. This certificate provides the necessary fundamentals in these areas and advanced concepts and applications in integrated circuit design, devices, and process technology. The program will also introduce the IC designer to state-of-the-art tools and techniques. The program consists of the courses listed below; students are required to complete a total of 16 units. Any change in the requirements must be approved by the academic advisor.

Digital Signal Processing and Machine Learning
Advisors: Dr. Maria Kyrarini, Dr. Tokunbo Ogunfunmi, Dr. Sally Wood

This certificate program provides a basic understanding of digital signal processing theory, machine learning and modern implementation methods as well as advanced knowledge of at least one specific application area. Digital signal processing and machine learning have become important across many areas of engineering, and this certificate prepares students for traditional or novel applications.

Digital Signal Processing Theory
Advisors: Dr. Tokunbo Ogunfunmi, Dr. Sally Wood

This certificate program provides a firm theoretical grounding in fundamentals of digital signal processing (DSP) technology and its applications. It is appropriate for engineers involved with any application of DSP who want a better working knowledge of DSP theory and its applications. A novel feature of the program is a hands-on DSP hardware/software development laboratory course in which students design and build systems for various applications using contemporary DSP hardware and development software.

Fundamentals of Electrical and Computer Engineering
Advisor: Dr. Shoba Krishnan

This certificate has been designed for those individuals who have significant work experience in some area of electrical and computer engineering and wish to take graduate-level courses but may lack some prerequisite knowledge because they have not earned a BS degree in electrical and/or computer engineering. This one-year program consists of 16 to 28 units, depending on the background of the individual student, and covers electrical and computer engineering core areas. Units from courses at or above the 200 level may be credited toward the Master of Science Degree in Electrical and Computer Engineering after successful completion of the certificate.

RF and Applied Electromagnetics
Advisor: Dr. Kurt Schab

The purpose of this certificate is to meet the increasing need for the knowledge in microwave, antenna and RF integrated circuits in existing electronic products. This program is offered for students who have a B.S. in Electrical Engineering. Students are expected to have knowledge of multivariate calculus and preferably partial differential equations and they must ensure that they have prerequisites for the courses in their program.

The curriculum consists of 16 units: two required courses (4 units) and 12 units of elective courses listed below:

Electrical and Computer Engineering Laboratories

The Electrical and Computer Engineering program is supported by a set of well-equipped laboratories. Some are dedicated solely for lower division courses such as circuits and electronics. In addition, the department has a diversity of research and teaching laboratories listed next.

The Electromagnetics and Communications Laboratory provides a full range of modern RF measurement capabilities up to 22 GHz, including a number of vector network analyzers, spectrum analyzers, and antenna measurement systems. This lab also includes complete production facilities for prototyping printed microwave circuits and antennas.  Further, the lab has extensive computer-aided design and simulation capability, including both commercial packages and research-grade in-house solvers. In both research and teaching, connections between physical hardware measurements and computer simulations are stressed.

The Computer Systems Laboratory offers various research projects in hardware-software co-design of digital systems. Examples of target designs include Internet-of-Things (IoTs), wearable devices, wireless sensor networks (WSNs), satellite on-board computers, neural network (NN) accelerators, and so on. Non-functional design concerns such as real-time, low-power, thermal behavior, security, or privacy are also important research topics studied in the Computer Systems Laboratory. The lab supports both graduate and undergraduate student research and has the following facilities to support student research: various FPGAs, MPSoC prototyping boards, GPU workstations (for NN training), and power monitoring tools. 

The IC Design and Technology Laboratory is dedicated to teaching and research topics on electronic materials and devices, integrated circuit design, and IC manufacturing technologies. Current research topics include modeling complex electronic devices using variational methodologies, materials and device characterizations, fabrication and experimental studies of photovoltaic devices, emission free smart infrastructure, and optimizing energy infrastructure.

The Complex Systems and Control Laboratory provides an experimental environment for students in the area of control system and power engineering. The lab includes computer-controlled DC motors. These motors provide students with a range of qualitative and quantitative experiments such as inverted pendulum for learning the utility and versatility of feedback in computer-controlled systems. Additionally, the lab is equipped with a state-of-the-art robotic arm mounted on a mobile robot. The students can learn how to program the robot to perform collaborative tasks with human teammates. The lab also has a Linux-based workstation with GPUs for simulating brain-inspired architectures using emergent memory nanodevices (memristors and memcapacitors) as synapses for artificial neural networks.

The Latimer Energy Laboratory (LEL) supports a very wide range of activities relating to solar energy, more specifically photovoltaics (PV) and management of renewable energy sources, from K-12 outreach through graduate engineering. The laboratory focuses on two major directions: 1) measurement and characterization of different renewable energy sources; and 2) integration of renewable energy into the electric grid. The lab has instrumentation such as pyranometers, VIS-IR spectrometers, metallurgical microscopes, source meters, grid simulator software and related computers.

The Thermal and Electrical Nanoscale Transport (TENT) Laboratory provides teaching and research facilities for modeling, simulation, and characterization of devices and circuits in the nanoscale. Ongoing research topics include silicon heterostructures, thin dielectrics, high-frequency device and circuit parameter extraction, carbon nanostructures used as electrical interconnect and thermal interface materials, and compact modeling of transistors and interconnects for large-scale circuit simulation. This laboratory is located inside NASA Ames Research Center in Moffett Field, California, and was established to conduct, promote, and nurture nanoscale science and technology interdisciplinary research and education activities at the University.

The Information Systems and Machine Learning Laboratory supports research in theoretical algorithm development in digital signal processing, adaptive and nonlinear signal processing, machine learning, deep learning, coding and information theory, private information retrieval, private function computation, secure and fault-tolerant distributed computing, group testing, and compressed sensing. Application areas include speech, audio, image and video processing for computer vision, communications, biological testing and diagnostics, artificial intelligence (AI), cloud computing, machine learning in the cloud, distributed storage systems, cache networks, and server-based and peer-to-peer networking.

The Human-Machine Interaction & Innovation (HMI2) Laboratory supports research in Human-Robot Interaction, Assistive Robotics, Intelligent Systems and Assistive Technologies with a special focus on enhancing Human Performance. The lab is equipped with several robotic systems, including mobile manipulators and humanoid robots. Additionally, the lab has several wearable sensors, such as electroencephalogram (EEG) and electrocardiogram (ECG), in order to develop AI-based intelligent systems that improve interactions between machines and humans.

Course Descriptions

Undergraduate course descriptions may be found in the Undergraduate Bulletin.

Graduate Courses

Some graduate courses may not apply toward certain degree programs. During the first quarter of study, students are urged to discuss the program of study they wish to pursue in detail with their faculty advisor.

ECEN 200. Electrical and Computer Engineering Graduate Seminars

Regularly scheduled seminars on topics of current interest in the fields of electrical and computer engineering and computer engineering. Consult the department office for detailed information. (1 or 2 units)

ECEN 201. Electromagnetic Field Theory I

Time-varying electromagnetic field concepts starting with Maxwell’s equations. Wave propagation in free space and in lossy media. Near and far-field effects. Fundamental theorems in electromagnetics. Transmission line propagation of harmonic waves and of pulse and transient signals. Dispersion effects. Prerequisites: An undergraduate electromagnetic field course. (2 units)

ECEN 202. Computational Electromagnetics

Numerical solution of Maxwell’s Equations for engineering problems. Foundations and mathematical development of finite difference time domain (FDTD) and method of moments (MoM) solvers. Methods for numerical validation and robust simulation-based experiment design. Prerequisite: ECEN 201. (2 units)

ECEN 203. Bio-Electromagnetics

Fundamentals of bioelectromagnetics. Tissue characterization, dielectrophoresis electrodes, RF/Microwave Interaction mechanisms in biological materials. Electromagnetic field absorption, and SAR, Power transfer in biological environment, On-body and implant antennas, microwave hyperthermia. Also listed as BIOE 203. Prerequisite: ECEN 201 (or equivalent) or BIOE 168/268. (2 units)

ECEN 204. Magnetic Circuits for Electric and Autonomous Vehicles

Fundamentals of magnetic circuits, transformers, DC motors, induction motors, transducers, stationary and mobile wireless charging. Prerequisite: Introduction to Electromagnetic Field Theory. (2 units)

ECEN 210. Signals, Circuits, and Systems

Continuous and discrete signals. Circuit equations and time response. Laplace transform. Difference equations and discrete systems. Z-transform. Convolution. Transfer function. Frequency response. Fourier series and transform. Matrix representations of circuits and systems. The notion of state. State transition matrix. State and output response. Equivalent to ECEN 110. May not be included in the minimum required units of Electrical and Computer Engineering courses. (2 units)

ECEN 211. Modern Network Analysis I

Graph theory and its applications to network matrix equations. Network component magnitude and frequency scaling. Network topology, graph theory, graph matrices, oriented and non-oriented graphs. Fundamental network laws. Topologically dependent matrix equations. Circuit simulation. N Planar and dual graphs. Nondegenerate network state equations. Prerequisites: AMTH 246 and knowledge of Laplace transforms. (2 units)

ECEN 216. Modern Network Synthesis and Design

Approximation and synthesis of active networks. Filter design using positive and negative feedback biquads. Sensitivity analysis. Fundamentals of passive network synthesis. Credit not allowed for both 112 and 216. Prerequisite: ECEN 210 or its undergraduate equivalent of ECEN 110. (4 units)

ECEN 217. Chaos Theory, Metamathematics and the Limits of Knowledge: A Scientific Perspective on Religion

Limitations of science are examined in the framework of nonlinear system theory and metamathematics. Strange attractors, bifurcations, and chaos are studied in some detail. Additional topics include an introduction to formal systems and an overview of Godel’s theorems. The mathematical background developed in the course is used as a basis for exploring the relationship between science, aesthetics, and religion. Particular emphasis islaced on the rationality of faith. Also listed as ECEN  160. Prerequisites: AMTH 106 or an equivalent course in differential equations, and a basic familiarity with MATLAB. (4 units)

ECEN 218. Quantum and Parallel Algorithms for Scientific Computing

Quantum and parallel computing are explored as paradigms for high performance scientific computing. Particular emphasis is placed on quantum algorithms and graph-theoretic methods for parallelizing the solution of large sparse systems of equations. Since a proper understanding of these topics requires a background in matrix theory, functional analysis, cryptology and number theory, these areas are covered in some detail. Also listed as ECEN 162. Prerequisites: AMTH 246 or equivalent, and familiarity with MATLAB. (4 units)

ECEN 219. Fundamentals of Computer-Aided Circuit Simulation

Introduction to the algorithms and principles used in circuit simulation packages (such as SPICE). Formation of equations for linear and nonlinear circuits. Detailed study of three different types of circuit analysis (AC, DC, and transient). Discussion of computational aspects, including sparse matrices, Newton’s method, numerical integration, and parallel computing. Applications to electronic circuits, active filters, and CMOS digital circuits. Course includes a number of design projects in which simulation software is written in Matlab and verified using SPICE. Credit not allowed for both 118 and 219. Prerequisites: ECEN 21, ECEN 100, and ECEN 115. (4 units)

ECEN 223. Digital Signal Processing System Development

Hands-on experience with hardware and software development for real-time DSP applications. Students design, program, and build a DSP application from start to finish. Such applications include image processing, speech/audio/video compression, multimedia, etc. The development environment includes Texas Instruments TMS320C6X development systems. Prerequisites: ECEN 234 or ECEN 233E and knowledge of “C” programming language. (4 units)

ECEN 226. Machine Learning and Signal Processing using FPGAs

Implementation of machine learning inference pipelines in an FPGA; signal processing and hardware architecture to take a trained network through to a hardware realization; overview of the latest generation FPGA technology and C++ High Level Synthesis (HLS) FPGA design flows. Students will learn how to implement, in fixed-point arithmetic, in hardware, the linear-algebra operations that are at the center of virtually all ML networks such as GoogleNet, ResNet and other well-known network architectures. Implementation of the common linear algebra functions and nonlinear functions that form the core components of many common networks will be covered. FPGA implementation of a multi-layer perceptron network and a CNN (convolutional neural network) accelerator using a HLS design flow. Prerequisites: (ECEN 133, ECEN 233E or ECEN 234) and (ECEN 127 or the equivalent) and C++ programming experience. (2 units)

ECEN 230. Introduction to Control Systems

Applications of control systems in engineering. Principle of feedback. Performance specifications: transient and steady-state response. Stability. Design of control systems by frequency and root-locus methods. Computer-controller systems. State-variable feedback design. Credit not allowed for both ECEN 130 and ECEN 230. Prerequisite: ECEN 210 or its undergraduate equivalent of ECEN 110. (4 units)

ECEN 231. Power System Stability and Control

Examine power system stability and power system control, including load frequency control, economic dispatch and optimal power flow. Also listed as ECEN 184. Prerequisite: ECEN 183 or equivalent. (4 units)

ECEN 232. Introduction to Nonlinear Systems

This course is an Introduction to nonlinear systems. Topics include introducing some nonlinear phenomena, phase-plane analysis including phase portraits, singular points, linearization, limit cycles, Poincare-Bendixson criteria, Lyapunov stability theorems, LaSalle's invariance principle, stability analysis of linear system via Lyapunov stability theorem, Lyapunov stability analysis of nonautonomous, and linear time-varying systems. Also listed as MECH 423. Prerequisite: MECH 323 or ECEN 236 or its equivalent. (2 units)

ECEN 233. Digital Signal Processing

Description of discrete signals and systems. Z-transform. Convolution and transfer functions. System response and stability. Fourier transform and discrete Fourier transform. Sampling theorem. Digital filtering. Also listed as CSEN 201. Prerequisite: ECEN 210 or its undergraduate equivalent of ECEN 110. (2 units)

ECEN 233E. Digital Signal Processing I and II

Same description as ECEN 233 and ECEN 234. Credit not allowed for both ECEN 133 and 233E. Also listed as CSEN 201E (4 units)

ECEN 234. Digital Signal Processing II

Continuation of ECEN 233. Digital FIR and IIR filter design and realization techniques. Multirate signal processing. Fast Fourier transform. Quantization effects. Also listed as CSEN 202. Prerequisite: ECEN 233. (2 units)

ECEN 235. Estimation I

Introduction to Classical estimation. Minimum Variance Unbiased Estimator (MVUE) from Cramer-Rao theorem, sufficient statistics, and linear estimator constraint. Maximum Likelihood Estimation (MLE) method. Least Square (LS) methods. Prerequisites: AMTH 211 or AMTH 212, AMTH 246 or AMTH 247, familiarity with MATLAB. (2 units)

ECEN 236. Modern Control Systems I       

Concept of state-space descriptions of dynamic systems. Relations to frequency domain descriptions. State-space realizations and canonical forms. Stability. Controllability and observability. State feedback and observer design. Also listed as MECH 323. Prerequisite: ECEN 130 or its undergraduate equivalent. (2 units)

ECEN 237. Optimal Control I

Introduction to the principles and methods of the optimal control approach: performance measure criteria including the definition of minimum-time, terminal control, minimum-control effort, tracking and regulator problems, calculus of variation applied to optimal control problems including Euler-Lagrange equation, transversality condition constraint, Pontryagin’s minimum principle (PMP), linear quadratic regulator (LQR) and tracking control problems. Also listed as MECH 429. Prerequisite: ECEN 236. Students are expected to be proficient in MATLAB/Simulink. (2 units)

ECEN 238. Model Predictive Control

Review of state-space model in discrete time, stability, optimal control, prediction, Kalman filter. Measurable and unmeasurable disturbance, finite and receding horizon control, MPC formulation and design. Also listed as MECH 420. Prerequisite: ECEN 237 or MECH 324 or equivalent. (2 units)

ECEN 239. Topics in Systems Theory

Various topics. (2 units)

ECEN 241. Introduction to Communication

Review of signals and systems in both time and frequency domain. Analog modulation and demodulation. The impact of noise on analog systems. Prerequisite: ECEN 210 or equivalent. (2 units)

ECEN 241E. Modern Communications

This course combines the topics found in ECEN 241 and ECEN 243 (both 2 unit courses) into one 4-unit course. Credit not allowed for both ECEN 241/243 and ECEN 241E. Prerequisites: ECEN 210 or equivalent and AMTH 108 or its equivalent. (4 units)

ECEN 243. Digital Communication Systems

Review of probability, random variables, and random processes. Digital modulation/demodulation techniques and their performance in the presence of noise. Prerequisite: ECEN 241 and AMTH 108 or equivalent. (2 units)

ECEN 244. Information Theory

Principles of information theory and error-correcting codes. Information-theoretic measures and their properties. Lossless source coding theorem and algorithms. Noisy channel models and channel coding theorem. Also listed as CSEN 341. Prerequisite: AMTH 211 or equivalent. (2 units)

ECEN 244E. Information Theory and Error-Correcting Codes

This course combines the topics found in ECEN 244 and ECEN 444 (both 2 unit courses) into one 4-unit course. Credit not allowed for both ECEN 244/444 and ECEN 244E. Prerequisite: AMTH 211 or its equivalent. (4 units)

ECEN 247. Communication Systems Modeling Using Simulink I

The objective of this course is for students to acquire and consolidate their practical skills of digital communication systems design through building simulation of some carefully selected prototype systems using MATLAB® and Simulink.® Examples include communication systems. The components and the principle of operation of each system will be presented in a lecture, together with key simulation techniques required. Topics include digital modulation and synchronization. Prerequisites: ECEN 233 and 243. (2 units)

ECEN 248. Communication Systems Modeling Using Simulink II

Continuation of ECEN 247. Prerequisite: ECEN 247. (2 units)

ECEN 249. Topics in Communication

Various topics. (2 units)

ECEN 250. Electronic Circuits

Introductory presentation of semiconductor circuit theory. The p-n junction, bipolar junction transistors (BJT), field-effect transistors and circuit models for these devices. DC biasing required of small-signal amplifier circuits. Analysis and design of small-signal amplifiers. The ideal operational amplifier and circuit applications. May not be taken for credit by a student with an undergraduate degree in electrical engineering. Not for graduate credit. Prerequisite: ECEN 50 or equivalent. (2 units)

ECEN 251. Transistor Models for IC Design

Semiconductor device modeling methods based upon device physics, process technology, and parameter extraction. Model derivation for bipolar junction transistors and metal-oxide semiconductor field-effect transistors for use in circuit simulators. Model parameter extraction methodology utilizing linear regression, data fitting, and optimization techniques. Prerequisite: ECEN 265 or ECEN 267. (2 units)

ECEN 252. Analog Integrated Circuits I

Design and analysis of multi-stage BJT and CMOS analog amplifiers. Study of differential amplifiers, current mirrors, and gain stages. Frequency response of cascaded amplifiers and gain-bandwidth considerations. Concepts of feedback, stability, and frequency compensation. Prerequisite: ECEN 115 or equivalent. (2 units)

ECEN 253. Analog Integrated Circuits II

Design of operational amplifiers and wideband amplifiers. Design of output stages and power amplifiers. Reference and biasing circuits. Study of noise and distortion in analog ICs and concepts of low noise design. Selected applications of analog circuits such as comparators. Prerequisite: ECEN 252. (2 units)

ECEN 254. Advanced Analog Integrated Circuit

Design and analysis of BJT and MOSFET analog ICs. Study of analog circuits such as comparators, sample/hold amplifiers, and continuous time switch capacitor filters. Architecture and design of analog to digital and digital to analog convertors. Reference and biasing circuits. Study of noise and distortion in analog ICs. Prerequisite: ECEN 116. Co-requisite: ECEN 117L. (4 units)

ECEN 259. Topics in Circuit Design

Various topics. (2 units)

ECEN 261. Fundamentals of Semiconductor Physics

Wave mechanics. Crystal structure and energy band structure of semiconductors. Carrier statistics and transport. Electrical and optical properties. (2 units)

ECEN 264. Semiconductor Device Theory I

Physics of semiconductor materials, junctions, and contacts as a basis for understanding all types of semiconductor devices. Prerequisite: ECEN 261 or ECEN 151 or equivalent. (2 units)

ECEN 265. Semiconductor Device Theory II

Continuation of ECEN 264. MOSFET basics, short-channel and high-field effects, CMOS, bipolar junction transistors. Prerequisite: ECEN 264. (2 units)

ECEN 266. Semiconductor Device Theory I and II

Same description as ECEN 264 and 265. Prerequisite: ECEN 261 or ECEN 151 or equivalent. Credit allowed for either ECEN 264 and 265, or ECEN 266. (4 units)

ECEN 267. Device Electronics for IC Design

Properties of materials, crystal structure, and band structure of solids. Carrier statistics and transport; p-n junction electrostatics, I-V characteristics, equivalent circuits. Metal-semiconductor contacts, Schottky diodes. MOS field-effect transistors, bipolar junction transistors.  This course covers the essential device concepts necessary for analog, digital, and/or mixed signal circuit design. Credit not allowed for both ECEN 151 and ECEN 267. Prerequisite or Co-requisite: ECEN 104 or basic knowledge of electrostatics. (4 units)

ECEN 270. Introduction to IC Materials

Materials issues in IC, classification of IC materials, Historical perspective. IC materials electrical conductivity, high-k, low-k materials. IC processing materials; solid liquid, gaseous dopants, chemicals and gasses for etching and cleaning; IC lithography materials; photo-, e-beam-, x-ray resists, resist developers; IC packaging materials; IC thin film materials; adhesion, thermal conductivity and stress, electrical conductivity and sheet resistance. (2 units)

ECEN 271. Microsensors: Components and Systems

Microfabrication technologies, bulk and surface micromachining, sensor fundamentals, electronic, chemical, and mechanical components as sensors, system level issues, technology integration; application and examples of sensors. (2 units)

ECEN 274. Integrated Circuit Fabrication Processes I

Fundamental principles of silicon-integrated circuit fabrication processes. Practical and theoretical aspects of microelectronic fabrication. Basic materials properties, including crystal structure and crystallographic defects; physical and chemical models of crystal growth; and doping, thermal oxidation, diffusion, and ion implantation. Prerequisite: ECEN 270. (2 units)

ECEN 275. Integrated Circuit Fabrication Processes II

Physical and chemical models of etching and cleaning, epitaxy, deposited films, photolithography, and metallization. Process simulation and integration. Principles and practical aspects of fabrication of devices for MOS and bipolar integrated circuits. Prerequisite: ECEN 270. (2 units)

ECEN 276. Integrated Circuit Fabrication Process Technology

Fundamental principles of processes essential for fabricating micro- and nanoelectronic   hardware ranging from Integrated circuits, MEMS and biosensors to power, control and optoelectronic devices. Physical and chemical models of semiconductor crystal growth, thermal oxidation and diffusion, ion implantation, Lithography, etching and cleaning, epitaxy, chemical and physical vapor deposition, metallization, etc.  Process integration and simulation using TCAD. Also listed as ECEN 152. Prerequisite: ECEN 270. (4 units)            

ECEN 276L. Integrated Circuit Fabrication Process Technology Laboratory

Laboratory for ECEN 276. Also listed as ECEN 152L. (1 unit)          

ECEN 277. IC Assembly and Packaging Technology

IC assembly techniques, assembly flow, die bond pad design rules, eutectic bonding and other assembly techniques, package types and materials, package thermal and electrical design and fabrication, special package considerations, future trends, and package reliability. Prerequisite: ECEN 201. (2 units)

ECEN 279. Topics in Semiconductor Devices and Processing

Various topics. (2 units)

ECEN 280. Introduction to Alternative Energy Systems

An introduction to such alternative energy systems with an emphasis on those utilizing solar technologies. Learn how the technologies work to provide electrical power today and the capabilities foreseen for the future. The material is designed to be suitable for both undergraduate and graduate students in engineering and related applied sciences. Also listed as MECH 287. (2 units)

ECEN 281A. Power Systems: Generation and Transmission

Electricity is the most versatile and widely used form of energy, and as such, it is the backbone of today’s and tomorrow’s global society. The course deals with the power system structure and components, electric power generation, transmission, and distribution. It also examines how these components interact and are controlled to meet the requirement of capacity, energy demand; reliability, availability, and quality of power delivery; efficiency, minimization of power loss; sustainability, and integration of low carbon energy sources. Prerequisite: ECEN 100 or equivalent. (2 units)

ECEN 281B. Power Systems: Distribution

The objective of this course is to cover the fundamental as well as wider aspects of Electric Power Transmission and Distribution networks including monitoring and control application tools typically provided by Energy Management Systems that enable electric utility companies to manage these assets to achieve their goals. Prerequisite: ECEN 281A. (2 units)

ECEN 282. Photovoltaic Devices and Systems

This course begins with a discussion of the sun as a source of energy, emphasizing the characteristics of insolation which then leads to a study of solar cells, their performance, their models, and the effects on their performance of factors such as atmospheric attenuation, incidence angle, shading, and others. Cells are connected together to become modules, which in turn are connected in arrays. This leads to a discussion of power electronic devices used to control and condition the DC solar voltage, including charge controllers, inverters, and other devices. Energy storage is studied. These components are then collected together in a solar PV system. The course concludes with a discussion of system sizing. (2 units)

ECEN 283. Characterization of Photovoltaic Devices

This course consists of five pre-lab lectures and five experiments exploring different aspects of photovoltaic cells and modules, including cell characterization under controlled conditions using a solar simulator; determining the spectral response and quantum efficiency of cells; measurement of solar irradiance and insolation; characterization of photovoltaic modules under real sun conditions; study of solar-related power electronics. Prerequisite: ECEN 282 or equivalent. (2 units)

ECEN 284. Solar Cell Technologies & Simulation Tools

Review of concepts needed to understand function, design, and manufacturing of PV cells and modules. PV cell physics leading to derivation of the I-V curve and equivalent circuit, along with contact and optical design, and use of computer-aided design tools. Manufacturing processes for silicon and thin film cells and modules. Cell measurements, including simulators, quantum efficiency, and parameter extraction. Cell types include silicon, thin film, organics, and concentrators. Markets, drivers, and LCOE (levelized cost of electricity) are surveyed. (2 units)

ECEN 284L. Solar Cell Technologies and Simulation Tools Laboratory

Co-requisite: ECEN 284. (1 unit)

ECEN 285. Introduction to the Smart Grid

The smart grid initiative calls for the construction of a 21st-century electric system that connects everyone to abundant, affordable, clean, efficient, and reliable electric power anytime, anywhere. It is envisioned that it will seamlessly integrate many types of generation and storage systems with a simplified interconnection process analogous to “plug and play.” This course describes the components of the grid and the tools needed to realize its main goals: communication systems, intelligent meters, and appropriate computer systems to manage the grid. Prerequisite: ECEN 50 or equivalent. (2 units)

ECEN 286. Introduction to Wind Energy Engineering

Introduction to renewable energy, history of wind energy, types and applications of various wind turbines, wind characteristics and resources, introduction to different parts of a wind turbine including the aerodynamics of propellers, mechanical systems, electrical and electronic systems, wind energy system economics, environmental aspects and impacts of wind turbines, and the future of wind energy. Also listed as MECH 286. (2 units)

ECEN 287. Energy Storage Systems

Energy storage systems play an essential role in the utilization of renewable energy. They are used to provide reserve power under different circumstances and needs such as peak shaving, load leveling, and ancillary services. Power electronics equipment converts the battery power into usable grid power. The course will survey batteries, pumped storage, flywheels, ultracapacitors, etc., with an analysis of the advantages and disadvantages, and uses of each. (2 units)

ECEN 288. Energy Management Systems

Energy Management Systems (EMS) is a class of control systems that electric utility companies utilize for three main purposes: monitoring, engagement, and reporting. Monitoring tools allow electric utility companies to manage their assets to maintain the sustainability and reliability of power generation and delivery. Engagement tools help in reducing energy production costs, transmission and distribution losses by optimizing utilization of resources and/or power network elements. Reporting tools to track operational costs and energy obligations. Also listed as CSEN 282. (2 units)

ECEN 289. Topics in Energy Systems

Various topics (2 units)

ECEN 296. Independent Study

Supervised study of specialized and/or advanced topics not covered by current course offerings. By arrangement. (1-6 units)

ECEN 297. Master’s Thesis Research

By arrangement. Limited to department majors only (1–9 units). A grade of “N” is assigned each quarter until the thesis is submitted. Upon thesis submission, all “N” grades are changed to a letter grade, signifying completion of the thesis research. Prerequisite: ECEN 299 (6 units)

ECEN 298. Ph.D. Thesis Research

By arrangement. Limited to department Ph.D. students only. A nominal number of 36 units is expected toward the Ph.D. degree. (1–15 units per quarter)

ECEN 299. Directed Research

Supervised research not requiring a thesis. Limited to department majors only. By arrangement. (1–6 units)

ECEN 329. Introduction to Intelligent Control

Intelligent control, AI, and system science. Adaptive control and learning systems. Artificial neural networks and Hopfield model. Supervised and unsupervised learning in neural networks. Fuzzy sets and fuzzy control. Also listed as MECH 329. Prerequisite: ECEN 236. (2 units)

ECEN 330. Introduction to Stochastic Control for Supply and Demand Network

Managing inventories plays an important role in supply and demand network optimization. This course covers basic inventory models. The foundations needed to characterize optimal policies using deterministic and stochastic control strategies. Markov chain. Optimal control. Stochastic control. Prerequisites: Statistics, Probability, ECEN 238 or equivalent. (2 units)

ECEN 331. Autonomous Driving Systems

This course introduces students to autonomous driving systems. Through lectures, labs, and assignments, students will gain hands-on experience on the major modules of the system including localization, sensor fusion, perception, detection, segmentation, scene understanding, tracking, prediction, path planning, control, routing, and decision making. Prerequisites: First-year graduate standing in ECEN, CSEN or MECH and knowledge of programming. (2 units)

ECEN 331L. Autonomous Driving Systems Lab

Lab for Autonomous Driving Systems, ECEN 331. (1 unit)

ECEN 333. Digital Control Systems

Difference equations. Sampling. Quantization. Z-transform. Transfer functions. State-Space models. Controllability and observability. Stability. Pole-placement by feedback. Frequency response methods. Prerequisites ECEN 230 or 236. (2 units)

ECEN 334. Introduction to Statistical Signal Processing

Introduction to statistical signal processing concepts. Random variables, random vectors, and random processes. Second-moment analysis, estimation of first and second moments of a random process. Linear transformations; the matched filter. Spectral factorization, innovation representations of random processes. The orthogonality principle. Linear predictive filtering; linear prediction and AR models. Levinson algorithm. Burg algorithm. Prerequisites: AMTH 211 and ECEN 233 or ECEN 233E. (2 units)

ECEN 335. Estimation II

Introduction to Bayesian estimation. Minimum mean square error estimator (MMSE), Maximum a posteriori estimator (MAP). Wiener filter and Kalman filter. Prerequisite: ECEN 235. (2 units)

ECEN 336. Detection

Hypothesis testing. Neyman-Pearson lemma. Generalized matched filter. Detection of deterministic and random signals in Gaussian and non-Gaussian noise environments. Prerequisite: AMTH 362, ECEN 243, or ECEN 335. (2 units)

ECEN 337. Robotics I

Overview of robotics: control, AI, and computer vision. Components and structure of robots. Homogeneous transformation. Forward kinematics of robot arms. Denavit-Hartenberg representation. Inverse kinematics. Velocity kinematics. Manipulator Jacobian. Singular configurations. Euler Lagrange equations. Dynamic equations of motion of manipulators. Task planning, path planning, and trajectory planning in the motion control problem of robots. Also listed as MECH 337. Prerequisite: AMTH 245. (2 units)

ECEN 337L. Introduction to Robot Operating System (ROS)

Laboratory for Robot Programming using Python and Robot Operating System (ROS). Also listed as ECEN 131L. Prerequisite: Basic Programming (1 unit)

ECEN 338. Robotics II

Joint-based control. Linear control of manipulators. PID control and set-point tracking. Method of computer-torque in trajectory following control. Also listed as MECH 338. Prerequisites: ECEN 236 and 337. (2 units)

ECEN 339. Robotics III

Intelligent control of robots. Neural networks and fuzzy logic in robotic control. Selected topics of current research in robotics. Also listed as MECH 339. Prerequisite: ECEN 338. (2 units)

ECEN 345. Phase-Locked Loops

Basic loop. Components. Describing equations. Stability. Transients. Modulation and demodulation. Prerequisite: ECEN 130. (2 units)

ECEN 347. Advanced Digital Communication Systems

Receiver design, equalizers, and maximum likelihood sequence detection. Modulation and receiver design for wireline and wireless communications. Particular emphasis on intersymbol interference and equalizers. Offered every other year. Prerequisite: ECEN 243. (2 units)

ECEN 348. FPGA for Communications Applications

This course is a project-based course to introduce students to architectures and implementations of Field-Programmable Gate Arrays (FPGAs) for DSP for communications applications. Examples of a final project include implementing a significant application in communications such as Software-Defined Radio (SDR) or Wi-Fi. Prerequisites: ECEN 226 and 247. (2 units)

ECEN 351. RF Integrated Circuit Design

Introduction to RF terminology, technology tradeoffs in RFIC design. Architecture and design of radio receivers and transmitters. Low noise amplifiers, power amplifiers, mixers, oscillators, and frequency synthesizers. Prerequisites: ECEN  252 and 387. (2 units)

ECEN 352. Mixed Signal IC Design for Data Communications

Design and analysis of mixed-signal circuits for data communications. Introduction to data communications terminology and signaling conventions. Data transmission media, noise sources. Data transceiver design: Signal coding/decoding, transmit signal waveshaping, receive equalization. Timing Circuits: Clock generation and recovery techniques. Prerequisites: ECEN 252 and 387. (2 units)

ECEN 353. DC to DC Power Conversion

Basic buck, boost, and buck-boost DC to DC converter topologies in both continuous and discontinuous conduction modes (CCM and DCM). Analog and digital controlled pulse width modulation techniques. Efficiency and control loop stability analysis. Critical MOSFET parameters and non-ideal circuit behavior will be studied using time and frequency domain computer modeling. Prerequisites: ECEN 230 and ECEN 252 or 116. (2 units)

ECEN 354. Advanced RFIC Design

Design and analysis of passive circuits (filters, splitters, and couplers), Gilbert cell mixers, low phase noise VCOs, frequency translators, and amplifiers. Advanced simulation methods, such as envelope and time domain simulations. Class project designed to meet specifications, design rules, and device models of RFIC foundry. Prerequisite: ECEN 351. (2 units)

ECEN 359. Advanced Topics in Circuit Design

Various topics. (2 units)

ECEN 360. Nanomaterials

Physics, chemistry, and materials science of materials in the nanoscale. Thin films, inorganic nanowires, carbon nanotubes, and quantum dots are examples covered in detail as well as state-of-the-art synthesis processes and characterization techniques for these materials as used in various stages of technology development. Also listed as ENGR 262. Prerequisites: ENGR/GREN 260 and ECEN 261. (2 units)

ECEN 361. Nanoelectronics

Silicon-based technology in the sub-90nm regime. General scaling trend and ITRS Roadmap. Novel device architectures, logic and memory nanodevices, critical enabling device design and process technologies, interconnects, molecular electronics, and their potential usage in future technology nodes. Prerequisite: ECEN 265 or ECEN 267. (2 units)

ECEN 375. Semiconductor Surfaces and Interfaces

Structural and electronic properties of semiconductor surfaces, semiconductor/oxide interfaces, and metal/semiconductor interfaces. Relationship between interface morphology/composition and electrical properties. Modern techniques for characterizing surfaces and interfaces. Derivation of interface properties from electrical characterization of devices. Prerequisite: ECEN 265 or ECEN 267. (2 units)

ECEN 379. Topics in Micro/Nanoelectronics

Various Topics. (2 units)

ECEN 380. Economics of Energy

The focus of the course is the finances of power and energy, including applications of blockchain ledgers, and transactive energy. Roles of policy, regulation and markets that govern production and supply of electricity will be examined. Operational aspects of making and moving electricity are discussed and Levelized Cost of Energy (LOCE) models are developed. Distributed resource management, power flow optimization and integration of large-scale renewables will be considered. Prerequisite: ECEN 183 or ECEN 281A and ECEN 281B. (2 units)

ECEN 387. VLSI Design I

Introduction to VLSI design and methodology. Analysis of CMOS integrated circuits. Circuit modeling and performance evaluation supported by simulation (SPICE). Ratioed, switch, and dynamic logic families. Design of sequential elements. Full-custom layout using CAD tools. Also listed as CSEN 203. Prerequisite: CSEN/ECEN 127 or equivalent. (2 units)

ECEN 388. VLSI Design II

Continuation of VLSI design and methodology. Design of arithmetic circuits and memory. Comparison of semi-custom versus fully custom design. General concept of floor planning, placement, and routing. Introduction of signal integrity through the interconnect wires. Also listed as CSEN 204. Prerequisite: CSEN 203/ECEN 387 or equivalent, or ECEN 153. (2 units)

ECEN 389. VLSI Physical Design

Physical design is the phase that follows logic design, and it includes the following steps that precede the fabrication of the IC logic partitioning: cell layout, floor planning, placement, routing. These steps are examined in the context of very deep submicron technology. Effects of parasitic devices and packaging are also considered. Power distribution and thermal effects are essential issues in this design phase. Also listed as CSEN 305. Prerequisite: CSEN 204/ECEN 388 or equivalent. (2 units)

ECEN 390. Semiconductor Device Technology Reliability

Reliability challenges in device design, fabrication technology, and test methodology. Device design issues such as design tolerances for latch-up, hot carrier injection, and electromigration. Fabrication technology challenges for sub-micron processes. Test methodology in terms of design feasibility and high-level test/fault coverage. IC yield models and yield enhancement techniques. (2 units)

ECEN 391. Process and Device Simulation with Technology Computer Aided Design (TCAD)

Review of semiconductor technology fundamentals. TCAD tools and methods as a design aid for visualizing physical device quantities at different stages of design and influencing device process parameters and circuit performance. Introduction to numerical simulation and TCAD, 2D process and device simulation, CMOS process flow and device design, device characterization and parameter extraction, circuit simulation. Introduction to virtual IC factory concept, integration of process, device and circuit simulation tools. The concept of process variation, statistical analysis and modeling methods, such as Monte Carlo sampling, correlation analysis, response surface modeling. Prerequisite: ECEN 274. (2 units)

ECEN 421. Speech Coding I

Review of sampling and quantization. Introduction to Digital Speech Processing. Elementary principles and applications of speech analysis, synthesis, and coding. Speech signal analysis and modeling. The LPC Model. LPC Parameter quantization using Line Spectrum Pairs (LSPs). Digital coding techniques: Quantization, Waveform coding. Predictive coding, Transform coding, Hybrid coding, and Sub-band coding. Applications of speech coding in various systems. Standards for speech and audio coding. Also listed as CSEN 348. Prerequisite: ECEN 233 and/or 334 or equivalent. (2 units)

ECEN 422. Speech Coding II

Advanced aspects of speech analysis and coding. Analysis-by-Synthesis (AbS) coding of speech, Analysis-as-Synthesis (Aas) coding of speech. Code-Excited Linear Prediction speech coding. Error-control in speech transmission. Application of coders in various systems (such as wireless phones). International Standards for Speech (and Audio) Coding. Real-Time DSP implementation of speech coders. Speech recognition and Biometrics. Research project on speech processing. Also listed as CSEN 349. Prerequisite: ECEN 421. (2 units)

ECEN 423. Introduction to Voice-over-IP

Overview of voice encoding standards relevant to VoIP: G.711, G.726, G.723.1, G.729, G.729AB. VoIP packetization and signaling protocols: RTP/RTCP, H.323, MGCP/MEGACO, SIP. VoIP impairments and signal processing algorithms to improve QoS. Echo cancellation, packet loss concealment, adaptive jitter buffer, Decoder clock synchronization. Network convergence: Soft-switch architecture, VoIP/PSTN, interworking (Media and Signaling Gateways), signaling translation (SS7, DTMF/MF, etc.), fax over IP. Prerequisite: ECEN 233 or knowledge of basic digital signal processing concepts. (2 units)

ECEN 431. Adaptive Signal Processing I

Theory of adaptive filters, Wiener filters, the performance surface, gradient estimation. The least-mean-square (LMS) algorithm, other gradient algorithms, transform-domain LMS adaptive filtering, block LMS algorithm. IIR adaptive filters. The method of least squares. Recursive least squares (RLS) adaptive transversal filters; application of adaptive filters in communications, control, radar, etc. Projects. Prerequisites: ECEN 233 and ECEN 334 or AMTH 362 or knowledge of random processes. (2 units)

ECEN 431E. Adaptive Signal Processing I and II

Same description as ECEN 431 and ECEN 432. Prerequisite: ECEN 334 or AMTH 362 or knowledge of random processes. (4 units)

ECEN 432. Adaptive Signal Processing II

Linear prediction. Recursive least squares lattice filters. Applications of Kalman filter theory to adaptive transversal filters. Performance analysis of different algorithms. Fast algorithms for recursive least squares adaptive transversal filters. Applications of adaptive filters in communications, control, radar, etc. Projects. Offered in alternative years. Prerequisite: ECEN 431. (2 units)

ECEN 439. Topics in Adaptive Signal Processing

Various topics. (2 units)

ECEN 441. Communications Satellite Systems Engineering

Satellite systems engineering considerations. Spacecraft. Satellite link design. Communication systems techniques for satellite links. Propagation on satellite-earth paths. Earth station technology. Prerequisite: ECEN 243 or equivalent. (2 units)

ECEN 444. Error-Correcting Codes

Fundamentals of linear codes, block coding principles, convolutional codes, and modern coding techniques such as turbo codes and LDPC codes. Prerequisite: AMTH 211 or equivalent. (2 units)

ECEN 446. Introduction to Wireless Communication Systems

Overview of digital communications. Topics include bit rate and error performance. Long-term and short-term propagation effects. Link budgets. Diversity techniques. Prerequisite: Knowledge of random processes, AMTH 210, ECEN 241 or its equivalent. (2 units)

ECEN 446E Wireless Communications and Networking

This course combines the topics found in ECEN 446 and ECEN 447 into one 4-unit course. (4 units)

ECEN 447. Wireless Network Architecture

Issues in wireless management. Topics include: multiple access techniques, cellular and local area network standards, scheduling of users, handoff and channel assignment. Prerequisite: ECEN 446 or equivalent. (2 units)

ECEN 460. Advanced Mechatronics I

Theory of operation, analysis, and implementation of fundamental physical and electrical device components: basic circuit elements, transistors, op-amps, sensors, electro-mechanical actuators. Application to the development of simple devices. Also listed as MECH 207. Prerequisite: MECH 141 or ECEN 100. (3 units)

ECEN 461. Advanced Mechatronics II

Theory of operation, analysis, and implementation of fundamental controller implementations: analog computers, digital state machines, microcontrollers. Application to the development of closed-loop control systems. Also listed as MECH 208. Prerequisites: ECEN 460 or MECH 207, and MECH 217. (3 units)

ECEN 462. Advanced Mechatronics III

Electro-mechanical modeling and system development. Introduction to mechatronic support subsystems: power, communications. Fabrication techniques. Functional implementation of hybrid systems involving dynamic control and command logic. Also listed as MECH 209. Prerequisite: MECH 208 or ECEN 461. (2 units)

ECEN 500. Logic Analysis and Synthesis

Analysis and synthesis of combinational and sequential digital circuits with attention to static, dynamic, and essential hazards. Algorithmic techniques for logic minimization, state reductions, and state assignments. Decomposition of state machine, algorithmic state machine. Design for test concepts. Also listed as CSEN 200. Prerequisite: ECEN 127C or equivalent. (2 units)

ECEN 501. Embedded Systems

Embedded Systems are computing systems that measure, control, and interact. This course considers cost, speed, and power optimizations in design. The course and accompanying lab will create real systems with physical device interfaces and consider real-time behaviors. The course will design with embedded development environments, and explore bare-metal programming and debugging techniques, and embedded system validation. Co-requisite: ECEN 501L. (2 units)

ECEN 501L. Embedded Systems Lab

Lab projects based on an embedded computer module to practical applications that reinforce class concepts and provide some opportunities for creative design. Co-requisite: ECEN 501. (1 unit)

ECEN 502. Real-Time Systems

Formal methods and practical solutions related to embedded computing systems with time-critical deadlines. This includes hard real-time systems such as vehicular control and industrial machinery as well as soft real-time systems such as audio streaming or video games. Distributed real-time, timing analysis, and adaptation. Prerequisites: A grade of C- or better in ECEN 501 or equivalent. (2 units)

ECEN 503. Hardware-Software Codesign

The design, analysis, and verification of mixed hardware-software systems focusing on model of computations, the design of hardware-software interfaces, hardware/software partitioning, hardware-software co-simulation,  and transaction level modeling. Practical design examples such as optimizing hardware-software partitioning through integer linear programming (ILP) or genetic algorithms (GA), and platform-based design are covered. Prerequisite: A grade of C- or better in ECEN 502 or equivalent. (2 units)

ECEN 510. Computer Architecture Fundamentals

Computer instruction definition and formatting, the use of opcodes and operands. Instruction execution, control transfer. Pipelining. Hazards. Caches. Prerequisites: A grade of C- or better in either CSEN or ECEN 21, or equivalent. (2 units)

ECEN 511. Advanced Computer Architecture

Advanced architectural concepts built upon fundamentals. Superscalar and out-of-order execution for instruction-level parallelism and advanced branch prediction techniques. Vector architecture and Single Instruction Multiple Data (SIMD) extensions for data-level parallelism. Prerequisite: ECEN 122 or CSEN 122 or ECEN 510 or equivalent. (2 units)

ECEN 512. Advanced Computer Architecture II

Continuation of advanced architectural concepts. Memory system implementation concepts. Multiprocessing, including multi-core and multithreaded architectures. Shared memory and cache coherence. More on cache coherence protocols. Multi-level cache hierarchies. Memory consistency and synchronization. GPU architectures and Domain-Specific Architectures such as TPU. Prerequisite: ECEN 511 or equivalent. (2 units)

ECEN 513. Parallel System Architectures

Exploration of alternative computing architectures and their uses. SIMD computing. GPUs. Deep Learning accelerators. Warehouse-scale computing. Prerequisite: ECEN 511 or equivalent. (2 units)

ECEN 519. Special Topics in Advanced Computer Architecture

Support for virtual memory, shared memory synchronization, transactional memory, multithreading, chip multiprocessors, deep learning, SIMD, warehouse-scale computing. (2 units)

ECEN 520. Introduction to Machine Learning

Classification models, cross-validation; supervised learning, linear and logistic regression, support vector machines; unsupervised learning, dimensionality reduction methods; tree-based methods, and kernel methods; principal component analysis, K-means; reinforcement learning. Prerequisites: Python programming, elementary statistics. Co-requisites: ECEN 520L. (2 units)

ECEN 520L. Introduction to Machine Learning Laboratory

Laboratory component of ECEN 520. Co-requisite: ECEN 520. (1 unit)

ECEN 521. Deep Learning

Convolutional neural networks; analysis of selected architectures: GoogleNet, ResNet, Moblenet, Capsule networks; transfer learning; recurrent neural networks and applications; autoencoders; adversarial generative networks. Prerequisite: ECEN 520. Co-requisite: ECEN 521L. (2 units)

ECEN 521L. Deep Learning Laboratory

Laboratory component of ECEN 521. Co-requisite: ECEN 521. (1 unit)

ECEN 522. Reinforcement Learning

Introduction to the foundational ideas of reinforcement learning, which provides a way to model the interaction of autonomous agents with the world and emphasizes learning without supervision, and often without any knowledge of the rules of the task it is trying to learn; Markov decision processes, value functions, Monte Carlo estimation, dynamic programming, temporal difference learning, function approximation, scaling to large domains. Prerequisite: ECEN 521. (3 units)

ECEN 523. Natural Language Processing with Deep Learning

Computational properties of natural language; simple word level to syntactic level; design and implementation of neural network models used in NLP for applications such as question answering, language translation, language understanding, and natural language generation. Prerequisite: ECEN 521. (2 units)

ECEN 530. Hardware Security and Trust

New techniques for securing hardware from malicious attacks. Hardware security primitives. Hardware Trojan detection and prevention. Hardware-based obfuscation techniques. Side-channel attacks and countermeasures. Cryptographic algorithms. FPGA security. Hardware Metering. Watermarking. IP piracy. IoT security. Counterfeit detection and prevention. Prerequisite: ECEN 127 OR ECEN 603 with a grade of C- or better. (2 units)

ECEN 532. Design of Assistive Technologies

Accessible and Interactive Design. Design of Assistive Technologies. Prototype Development. Data Gathering. Data Analysis, Interpretation, and Representation. Project-based course. Also listed as ECEN 132. (2 units)

ECEN 601. Low Power Designs of VLSI Circuits and Systems

Design of digital circuits for reduced power consumption. Sources of power consumption in ICs and analysis algorithms for their estimation at different stages of design. Various power reduction techniques and their trade-offs with performance, manufacturability, and cost are analyzed. Project to design a digital circuit with power reduction as the primary objective. Prerequisite: ECEN 387. (2 units)

ECEN 602. Modern Time Analysis

Analysis in logic design review of background materials and introduction of concepts of false path, combinational delay, and minimum cycle time of finite state machines. Study of efficient computational algorithms. Examination of retiming for sequential circuits, speed/area trade-off. Prerequisite: ECEN 500. (2 units)

ECEN 603. Logic Design Using HDL

Algorithmic approach to design of digital systems. Use of hardware description languages for design specification. Structural, register transfer, and behavioral views of HDL. Switch-level modeling. Multiple model cross-validation. Simulation and synthesis of systems. Prior HDL experience is expected. Also listed as CSEN 303. Prerequisite: ECEN 127 or equivalent. (2 units)

ECEN 608. Design for Testability

Principles and techniques of designing circuits for testability. Concept of fault models. The need for test development. Testability measures. Ad hoc rules to facilitate testing. Easily testable structures, PLAs. Scan-path techniques, full and partial scan. Built-in self-testing (BIST) techniques. Self-checking circuits. Use of computer-aided design (CAD) tools. Also listed as CSEN 308. Prerequisite: ECEN 500 or equivalent. (2 units)

ECEN 609. Mixed-Signal DA and Test

Mixed-Signal test techniques using PLL and behavioral testing as major examples. Overview of the IEEE 1149.4 Mixed-Signal standard. Mixed-Signal DFT and BIST techniques with emphasis on test economics. Most recent industrial mixed-signal design and test EDA tools and examples of leading state-of-the-art SoCs. Prerequisites: ECEN 500 or CSEN 200 and ECEN 387 or CSEN 203. (2 units)

ECEN 613. SoC (System-on-Chip) Verification

This course presents various state-of-the-art verification techniques used to ensure the corrections of the SoC (System-on-Chip) design before committing it to manufacturing. Both Logical and Physical verification techniques will be covered, including Functional Verification, Static Timing, Power, and Layout Verification. Also, the use of Emulation, Assertion-based Verification, and Hardware/Software Co-Verification techniques will be presented. Also listed as CSEN 207. Prerequisites: ECEN 500 or CSEN 200 and ECEN 603 or equivalent. (2 units)

ECEN 617. Storage Systems – Technology and Architecture

The course will address the developments in storage systems. Increase in data storage has led to an increase in storage needs. This arises from the increase of mobile devices as well as increase in internet data storage. This course will provide the students good knowledge of different storage systems as well as challenges in data integrity. A discussion of the next generation of storage devices and architectures will also be done. (2 units)

ECEN 620. Digital Systems Design Project

By arrangement. An individual or group project that progresses through multiple phases of a complete design flow, leveraging and applying concepts learned in other courses. Projects can be pure hardware designs, or hardware/software co-designs. Prerequisites: ECEN 501, ECEN 511, ECEN 603. (1-6 units)

ECEN 624. Signal Integrity in IC and PCB Systems

Analysis, modeling, and characterization of interconnects in electronic circuits; Transmission line theory; losses and frequency dependent parameters. Signal Integrity issues in high-speed/ high-frequency circuits; means of identifying signal integrity problems. Reflection and crosstalk; analysis of coupled-line systems. Power distribution networks in VLSI and PCB environments and power integrity. Signal/Power integrity CAD. Prerequisite: ECEN 201. (2 units)

ECEN 639. Audio and Speech Compression

Audio and speech compression. Digital audio signal processing fundamentals. Non-perceptual coding. Perceptual coding. Psychoacoustic model. High-quality audio coding. Parametric and structured audio coding. Audio coding standards. Scalable audio coding. Speech coding. Speech coding standards. Also listed as CSEN 339. Prerequisites: AMTH 245 and CSEN 279 or equivalent. (2 units)

ECEN 640. Digital Image Processing I

Digital image representation and acquisition, color representation; point and neighborhood processing; image enhancement; morphological filtering; Fourier, cosine and wavelet transforms. Also listed as CSEN 340. Prerequisite: ECEN 233 or equivalent. (2 units)

ECEN 641. Image and Video Compression

Image and video compression. Entropy coding. Prediction. Quantization. Transform coding and 2-D discrete cosine transform. Color compression. Motion estimation and compensation. Digital video. Image coding standards such as JPEG and JPEG family. Video coding standards such as the MPEG series and the H.26x series. H.264/MPEG-4 AVC coding. HEVC/H 265/MPEG-H Part 2 coding. VVC. Future JVET standard Rate-distortion theory and optimization. Visual quality and coding efficiency. Brief introduction to 3D video coding and 3D-HEVC. Deep learning approaches. Applications. Also listed as CSEN 338. Prerequisites: AMTH 108, AMTH 245, basic knowledge of algorithms. (4 units)

ECEN 642. Computational and Medical Imaging

Algorithms for indirect image formation using both optimization and model-based methods. Application includes computed tomography, magnetic resonance imaging, microscopy, remote sensing, super-resolution. Fourier-based and sparse iterative algorithms. Analysis of accuracy and resolution of image formation based on measurement geometry and statistics. Offered in alternate years. Also listed as BIOE 642. Prerequisites: AMTH 211 and either ECEN 233 or AMTH 358 or equivalent. (2 units)

ECEN 643. Digital Image Processing II

Image restoration using least squares methods in image and spatial frequency domains; matrix representations; blind deconvolution; super-resolution methods; reconstructions from incomplete data; image segmentation methods, three-dimensional models from multiple views. Also listed as CSEN 343. Prerequisite: CSEN 340. (2 units)

ECEN 644. Computer Vision I

Introduction to image understanding, feature detection, description, and matching; feature based alignment; structure from motion stereo correspondence. Also listed as CSEN 344. Prerequisites: ECEN 640 and knowledge of linear algebra. (2 units)

ECEN 645. Computer Vision II

Learning and inference in vision; regression models; deep learning for vision; classification strategies; detection and recognition of objects in images. Also listed as CSEN 345. Prerequisites: ECEN 640 and knowledge of probability. (2 units)

ECEN 649. Topics in Image Processing and Analysis

Various topics. (2 units)

ECEN 701. RF and Microwave Systems

The purpose of this class is to introduce students to the general hardware components, system parameters, and architectures of RF and microwave wireless systems. Practical examples of components and system configurations are emphasized. Communication systems are used to illustrate the applications. Other systems, such as radar, the global positioning system (GPS), RF identification (RFID), and direct broadcast systems (DBS) are introduced. (2 units)

ECEN 706. Microwave Circuit Analysis and Design

Microwave circuit theory and techniques. Emphasis on passive microwave circuits. Planar transmission lines. Field problems formulated into network problems for TEM and other structures, scattering and transmission parameters, Smith chart, impedance matching, and transformation techniques. Design of power dividers, couplers, hybrids and microwave filters. Microwave CAD. Prerequisite: ECEN 201. (4 units)

ECEN 711. Active Microwave Devices I

Scattering and noise parameters of microwave transistors, physics of silicon bipolar and gallium arsenide MOSFET transistors, device physics, models, and high-frequency limitations. Applications to microwave amplifier and oscillator designs. Prerequisite: ECEN 706. (2 units)

ECEN 712. Active Microwave Devices II

Continuation of ECEN 711. Nonlinear active circuits and computer-aided design techniques. Nonlinear models of diodes, bipolar transistors and FET’s applied to the design of frequency converters, amplifiers, and oscillators. Techniques. Prerequisite: ECEN 711. (2 units)

ECEN 715. Antennas I

Fundamentals of radiation, antenna pattern, directivity and gain. Dipole and wire antennas. Microstrip Patch Antennas. Broadband antennas. Antennas as components of communications and radar systems. Antenna measurement. Antenna CAD. Prerequisite: ECEN 201. (2 units)

 ECEN 715E. Antenna Theory and Design

This course combines the topics found in ECEN (715 and ECEN 716 (both 2 unit courses) into one 4-unit course. Fundamentals of radiation, antenna pattern, directivity and gain. Dipole and wire antennas. Microstrip Patch Antennas. Broadband antennas. Antennas as components of communications and radar systems. Aperture antennas. Traveling-wave antennas. Antenna Arrays. Linear arrays with uniform and non-uniform excitations. Beam scanning and phased arrays; Planar arrays; Array Synthesis. (4 units)

ECEN 716. Antennas II

Continuation of ECEN 715. Aperture antennas. Traveling-wave antennas. Antenna Arrays. Linear arrays with uniform and non-uniform excitations. Beam scanning and phased arrays; Planar arrays; Array Synthesis. Prerequisite: ECEN 715. (2 units)

ECEN 717. Antennas III

Continuation of ECEN 716. Reflector, and lens antennas. Large antenna design. High-frequency techniques. Geometrical optics. Physical optics. Diffraction. Antenna synthesis. Offered in alternate years. Prerequisite: ECEN 716. (2 units)

ECEN 725. Optics Fundamentals

Fundamental concepts of optics: geometrical and wave optics. Optical components–-free space, lenses, mirrors, prisms. Optical field and beams. Coherent (lasers) and incoherent (LED, thermal) light sources. Elements of laser engineering. Optical materials. Fiber optics. Polarization phenomena and devices. Also listed as PHYS 113. Prerequisite: ECEN 201 or equivalent. (4 units)

ECEN 726. Microwave Measurements, Theory, and Techniques

Theory comprises six classroom meetings covering signal flow graphs, error models and corrections, S-parameter measurements, Vector analyzers, microwave resonator measurements, noise figure measurements, signal generation and characterization, spectrum analyzers, and phase noise measurements. Four laboratory meetings. Offered in alternate years. Prerequisite: ECEN 711. (3 units)

ECEN 729. Topics in Electromagnetics and Optics

Selected advanced topics in electromagnetic field theory. Prerequisite: As specified in class schedule. (2 units)

ECEN 809. Special Topics in Human-Machine Interaction

Selected advanced topics in Human-Machine Interaction. Prerequisite: As specified in class schedule. (2-4 units)

ECEN 921C. Introduction to Logic Design

Boolean functions and their minimization. Designing combinational circuits, adders, multipliers, multiplexers, decoders. Noise margin, propagation delay. Bussing. Memory elements: latches and flip-flops; timing; registers; counters. Introduction to FPGAs and the need for the use of HDL. Taught in the graduate time format. Foundation course not for graduate credit. Also listed as CSEN 921C. (2 units)