Students with background in other scientific fields are encouraged to apply to the graduate program in Electrical Engineering. Those applicants lacking minimum undergraduate preparation in the above areas may be admitted but will be required to take the appropriate undergraduate courses. Under special circumstances, students who have not completed all undergraduate requirements may be admitted provided that the deficiencies are corrected within the first year of graduate study. Courses taken for this purpose do not count towards an advanced degree.

Lecture, three hours. Prerequisite(s): MATH 046, PHYS 040C (both may be taken concurrently); concurrent enrollment in EE 01LA. Ohm's law and Kirchoff's laws; nodal and loop analysis; analysis of linear circuits; network theorems; transients in RLC circuits. Application of SPICE to circuit analysis.

EE 001B. Engineering Circuit Analysis II. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 001A and EE 01LA. Sinusoidal steady state analysis, polyphase circuits, magnetically coupled networks, frequency characteristics, Laplace and Fourier transforms, Laplace and Fourier analysis. Application of SPICE to complicated circuit analysis.

EE 01LA. Engineering Circuit Analysis I Laboratory. (1)

Laboratory, three hours. Prerequisite(s): EE 001A (may be taken concurrently). Laboratory experiments closely tied to the lecture material of EE 001A: resistive circuits, attenuation and amplification, network theorems and superposition, operational amplifiers, transient response, application of SPICE to circuit analysis.

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 001B. Electronic systems, linear circuits, operational amplifiers, diodes, nonlinear circuit applications, junction and metal-oxide-semiconductor field-effect transistors, bipolar junction transistors, MOS and bipolar digital circuits. Laboratory experiments are performed in the subject areas and SPICE simulation is used.

EE 100B. Electronic Circuits. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 100A. Differential and multistage amplifiers, output stages and power amplifiers, frequency response, feedback, analog integrated circuits, filters, tuned amplifiers, and oscillators. Laboratory experiments are performed in the subject areas and SPICE simulation is used.

EE 102. Analog Integrated Circuits. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 100B. Design, analysis, and application of analog integrated circuits. Topics include introduction to integrated circuit fabrication, IC active filters and switched-capacitor circuits, current-feedback, Norton and transconductance operational amplifiers, voltage comparators and regulators, video amplifiers, and phase-locked loops.

EE 105. Modeling and Simulation of Dynamic Systems. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): CS 010, EE 001A, MATH 046. Introduction to the mathematical modeling of dynamical systems and their methods of solution. Advanced techniques and concepts for analytical modeling and study of various electrical, electronic, and electromechanical systems based upon physical laws. Emphasis on the formulation of problems via differential equations. Numerical methods for integration and matrix analysis problems. Case studies. Digital computer simulation.

EE 110A. Signals and Systems. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): CS 010; EE 001B (may be taken concurrently); MATH 046. Basic signals and types of systems, linear time-invariant (LTI) systems, Fourier analysis, frequency response, and Laplace transforms for LTI systems. Laboratory experiments with signals, transforms, harmonic generation, linear digital filtering, and sampling/aliasing.

EE 110B. Signals and Systems. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 110A. Fourier analysis for discrete-time signals and systems, filtering, modulation, sampling and interpolation, z-transforms. Laboratory experiments with signals, transforms, harmonic generation, linear digital filtering, and sampling/aliasing.

EE 115. Introduction to Communication Systems. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 001B and EE 110B. Spectral density and correlation, modulation theory, amplitude, frequency, phase and analog pulse modulation and demodulation techniques, signal-to-noise ratios, and system performance calculations. Laboratory experiments in techniques of modulation and demodulation.

EE 116. Engineering Electromagnetics. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 001B (may be taken concurrently). Transmission lines, fields and field operators, electrostatic and magnetostatic fields, time-varying fields, electrodynamics, electromagnetic waves, plane waves, guided waves, and applications to engineering problems.

EE 117. Electromagnetics II. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 116. Applications of Maxwell's equations. Skin effect, boundary-value problems, plane waves in lossy media, transverse EM waves, hollow metal waveguides, cavity resonators, microstrips, propagation in dielectrics and optical fibers, optical fibers applications, radiation, and antennas. Laboratory work involves both software simulations and hardware experiments in basic electromagnetic technology.

EE 118. Introduction to Electromagnetic Devices. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 116. An introduction to electromechanical devices for students interested in mechatronics, robotics, control, computer peripherals, and energy or power systems areas. Emphasizes rotational devices commonly used in low-power automation systems. Analyzes permanent magnet DC machines, two-phase induction, brushless DC, and stepper motors.

EE 120A. Logic Design. (5)

Lecture, three hours; laboratory, six hours. Prerequisite(s): CS 010. Number systems and binary codes. Boolean algebra. Digital circuits. Combinational and sequential logic design principles and practices. Combinational and sequential programmable logic devices. Computer-aided design (CAD) and engineering of digital systems. Cross-listed with CS 120A.

EE 120B. Introduction to Embedded Systems. (5)

Lecture, three hours; laboratory, eight hours. Prerequisite(s): CS 120A/EE 120A. A study of design methodology and digital systems at the register and processor level. Topics include arithmetic processors, microprocessor architecture, memory, input/output (I/O) support, and peripherals. Studies digital to analog (D/A) and analog to digital (A/D) convertors, serial and parallel data transmission, memory access, and microprocessor-based digital systems. Cross-listed with CS 120B.

EE 128. Data Acquisition, Instrumentation, and Process Control. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): CS 120A/EE 120A, EE 100B; or consent of instructor. Analog signal transducers, conditioning and processing; step motors, DC servo motors, and other actuation devices; analog to digital and digital to analog converters; data acquisition systems; microcomputer interfaces to commonly used sensors and actuators; design principles for electronic instruments, real time process control and instrumentation.

EE 132. Automatic Control. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 110A or ENGR 118 or consent of instructor. Mathematical modeling of linear systems for time and frequency domain analysis. Transfer function and state variable representations for analyzing stability, controllability, and observability. Closed-loop control design techniques by Bode, Nyquist and root-locus diagrams. Laboratories involve both simulations and hardware.

EE 133. Solid-State Electronics. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 100A. Presents the fundamentals of solid-state electronics. Topics include electronic band structure, Fermi and quasi-Fermi levels; doping; contacts; junctions; field-effect, bipolar, and metal-oxide-semiconductor (MOS) transistors; and charge-coupled devices. Also reviews device fabrication concepts.

EE 140. Computer Visualization. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): CS 130. Visual perception and thinking, operations on digital images, shaded pictures, perspective transformation, picture generation using solid polyhedra, illumination and color models, ray tracing, special effects and animation. Laboratories on visual realism methods: dithering, halftoning, 3-D viewing, and rendering.

EE 141. Digital Signal Processing. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 110B. Transform analysis of Linear Time-Invariant (LTI) systems, discrete Fourier Transform (DFT) and its computation, Fourier analysis of signals using the DFT, filter design techniques, structures for discrete-time systems. Laboratory experiments on DFT, fast Fourier transforms (FFT), infinite impulse response (IIR), and finite impulse response (FIR) filter design, and quantization effects.

EE 143. Multimedia Technologies and Programming. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): CS 010 or knowledge of an object-oriented or fourth-generation (scripting) programming language, for example, C++, Hypertalk, Supertalk, Lingo, Openscript, ScriptX. Introduces multimedia technologies and programming techniques, multimedia hardware devices, authoring languages and environments, temporal and nontemporal media (interactivity in text, graphics, audio, video, and animation), applications, and trends. A term project is required. Cross-listed with CS 143.

EE 144. Introduction to Robotics. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 132. Basic robot components from encoders to microprocessors. Kinematic and dynamic analysis of manipulators. Open-and closed-loop control strategies, task planning, contact and noncontact sensors, robotic image understanding, and robotic programming languages. Experiments and projects include robot arm programming, robot vision, and mobile robots.

EE 146. Computer Vision. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): senior standing in Computer Science or Electrical Engineering, or consent of instructor. Imaging formation, early vision processing, boundary detection, region growing, two-dimensional and three-dimensional object representation and recognition techniques. Experiments for each topic are carried out.

EE 150. Digital Communications. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 115. Review of modulation, probability and random variables, correlation and power spectra, information theory, errors of transmission, equalization and coding methods, shift and phase keying; comparison of digital communication systems. Open-ended laboratory experiments include sampling, modulation, synchronization, and systems design.

EE 151. Introduction to Digital Control. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 132, EE 141. Review of continuous-time control systems; review of Z-transform and properties; sampled-data systems; stability analysis and criteria; frequency domain analysis and design; transient and steady-state response; state-space techniques; controllability and observability; pole placement; observer design; Lyapunov stability analysis. Laboratory experiments complementary to these topics include simulations and hardware design.

EE 152. Image Processing. (4)

Lecture, three hours; laboratory, three hours. Prerequisite(s): EE 110B. Digital image acquisition, image enhancement and restoration, image compression, computer implementation and testing of image processing techniques. Students gain hands-on experience of complete image processing systems, including image acquisition, processing, and display through laboratory experiments.

EE 175A-EE 175B. Senior Design Project. (4-4) W,S

Laboratory, nine hours; consultation, one hour. Prerequisite(s): senior standing in Electrical Engineering. Under the direction of a faculty member, students (individually or in small teams with shared responsibilities) propose, design, build, and test electrical engineering devices or systems. A written report, giving details of the project and test results, and an oral presentation of the design aspects are required. An In Progress (IP) grade is assigned for EE 175A. A letter grade is given for 175B.

EE 191 (E-Z). Seminar in Electrical Engineering. (1-4)

Seminar, one to four hours. Prerequisite(s): upper division standing or consent of instructor. Consideration of current topics in electrical engineering.

EE 194. Independent Reading. (1-2)

Extra reading, three to six hours. Prerequisite(s): upper division standing or consent of instructor. Independent reading in material not covered in course work. Normally taken in senior year. Course is repeatable to a maximum of 4 units.

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 133 or equivalent. Covers electronic devices and circuits including p-n junctions, field-effect transistors, heterojunction bipolar transistors, and nanostructures devices. Explores electrical and optical properties of semiconductor heterostructures, superlattices, quantum wires and dots, as well as devices and circuits based on these structures.

EE 201. Fundamentals of Semiconductors and Nanostructures. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 133. Examines principles of semiconductor materials and nanostructures. Topics include periodic structures, electron and phonon transport, defects, optical properties, and radiative recombination. Also covers absorption and emission of radiation in nanostructures, and nonlinear optics effects. Emphasizes properties of semiconductor superlattices, quantum wells, wires, and dots.

EE 210. Advanced Digital Signal Processing. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 110B, EE 141. Provides in-depth coverage of advanced techniques for digital filter and power spectral estimation. Topics include digital filter design, discrete random signals, finite-wordlength effects, nonparametric and parametric power spectrum estimation, multirate digital signal processing, least square methods of digital filter design, and digital filter applications.

EE 211. Adaptive Signal Processing. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 210, EE 215, EE 236. Provides an in-depth understanding of adaptive signal processing techniques. Covers Wold decomposition, Yule-Walker equations, spectrum estimation, Weiner filters, linear prediction, Kalman filtering, time-varying system tracking, nonlinear adaptive filtering, and performance analysis of adaptive algorithms and their variations including stochastic gradient, least mean square, least squares, and recursive least squares.

EE 215. Stochastic Processes. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 210, EE 235. A study of probability theory and stochastic processes, with a focus on the most fundamental aspect of modern communication, control, and signal processing systems driven by random signal inputs. Topics include random variables and stochastic processes; spectral analysis; Wiener optimum filter, matched filter, and Karhunen-Loeve expansion; mean square estimation theory including smoothing, filtering, and linear prediction; Levinson's algorithm, lattice filters, and Kalman filters; and the Markov process.

EE 224. Digital Communication Theory and Systems. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 115; MATH 149A-MATH 149B or STAT 160A-STAT 160B; or equivalents. Provides an overview of basic communication techniques and an introduction to optimum signal detection and correction. Topics include sampling and bandwidth; pulse code modulation; line coding and pulse shaping; delta modulation; stochastic approach to bandwidth and noise corruption; white Gaussian noise; matched filter; optimum signal detection; Shannon theorem; and error correction.

EE 225. Error-Correcting Codes. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 215, EE 224. Provides an overview of basic error-correcting techniques used in data transmission and storage. Topics include groups and Galois fields, error-correction capability and code design of Hamming codes, cyclic codes, Bose-Chaudhuri-Hocquengem (BCH) codes, and Reed-Solomon codes. Also considers concatenated design and decoding techniques.

EE 226. Wireless Communications. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 215, EE 224. Presentation of fundamental cellular concepts and new techniques in wireless communications. Topics include cellular systems and standards, frequency reuse, system capacity, channel allocation, cellular radio propagation, fading channel modeling and equalization, spread spectrum communications and other multiple access techniques, and wireless networking.

EE 235. Linear System Theory. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 132, MATH 113. Provides a review of linear algebra. Topics include the mathematical description of linear systems; the solution of state-space equations; controllability and observability; canonical and minimal realization; and state feedback, pole placement, observer design, and compensator design.

EE 236. State and Parameter Estimation Theory. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 235 or equivalent. Covers autoregressive and moving-average models, state estimation and parameter identification (including least square and maximum likelihood formulations), observability theory, synthesis of optimum inputs, Kalman-prediction (filtering and smoothing), steady-state and frequency domain analysis, on-line estimation, colored noise, and nonlinear filtering algorithms.

EE 237. Nonlinear Systems and Control. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 235. Explores nonlinear systems and control. Topics include nonlinear differential equations, second order nonlinear systems, equilibrium and phase portrait, limit cycle, harmonic analysis and describing function, Lyapunov stability theory, absolute stability, Popov and circle criterion, input-output stability, small gain theorem, averaging methods, and feedback linearization.

EE 238. Linear Multivariable Control. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 235. Investigates multivariable feedback systems, stability, performance, uncertainty, and robustness. Topics include analysis and synthesis via matrix factorization; Q-parameterization and all stabilizing controllers; frequency domain methods; and H(insert infinity) design and structured singular value analysis.

EE 239. Optimal Control. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 215, EE 235. Presents the theory of stochastic optimal control systems and methods for their design and analysis. Covers principles of optimization, Lagrange's equation, linear-quadratic-Gaussian control; certainty-equivalence; the minimum principle; the Hamilton-Jacobi-Bellman equation; and the algebraic Ricatti equation.

EE 240. Pattern Recognition. (4)

Lecture, three hours; outside research, three hours. Prerequisite(s): EE 141 or consent of instructor. Covers basics of pattern recognition techniques. Topics include hypothesis testing, parametric classifiers, parameter estimation, nonparametric density estimation, nonparametric classifiers, feature selection, discriminant analysis, and clustering.

EE 241. Advanced Digital Image Processing. (4)

Lecture, three hours; outside research, three hours. Prerequisite(s): EE 152 or consent of instructor. Covers advanced topics in digital image processing. Examines image sampling and quantization, image transforms, stochastic image models, image filtering and restoration, and image data compression.

EE 242. Intelligent Systems. (4)

Lecture, three hours; outside research, three hours. Prerequisite(s): graduate standing or consent of instructor. Introduces fundamental concepts of design of intelligent systems. Topics include biological versus computational systems, knowledge representation, computational reasoning, computational learning, language and human-machine communication, expert systems, computational vision, and examples of intelligent machines.

EE 243. Advanced Computer Vision. (4)

Lecture, three hours; outside research, three hours. Prerequisite(s): EE 146 or consent of instructor. A study of three-dimensional computer vision. Topics include projective geometry, modeling and calibrating cameras, representing geometric primitives and their uncertainty, stereo vision, motion analysis and tracking, interpolating and approximating three-dimensional data, and recognition of two-dimensional and three-dimensional objects.

EE 244. Computational Learning. (4)

Lecture, three hours; outside research, three hours. Prerequisite(s): graduate standing or consent of instructor. Explores fundamental computational learning techniques. Topics include elements of learning systems, inductive learning, analytic learning, case-based learning, genetic learning, connectionist learning, reinforcement learning and integrated learning techniques, and comparison of learning paradigms and applications.

EE 245. Advanced Robotics. (4)

Lecture, three hours; discussion, one hour. Prerequisite(s): EE 144, EE 235. Topics include robotics, mechatronics, and automation systems; design and analysis; mechanics; sensing and programming; linear and non-linear control; rigid and flexible systems; redundant robots; perception-driven action; multiarm cooperation; distributed autonomous robotic systems; programming languages and tools; simulations techniques; and application to mechatronics, manufacturing, and biomorphic systems.

EE 250. Information Theory. (3)

Seminar, three hours. Prerequisite(s): EE 215, EE 225. Provides an overview of general limitations imposed on communication systems. Topics include source and channel models, information as a stochastic concept, coding for discrete sources, stochastic models for discrete channels, coding theorems for channels with noise, and coding techniques for block and convolutional codes. Satisfactory (S) or No Credit (NC) grading is not available.

EE 259. Colloquium in Electrical Engineering. (1)

Colloquium, one hour. Prerequisite(s): graduate standing. Lectures on current research topics in electrical engineering presented by faculty members and visiting scientists. Graded Satisfactory (S) or No Credit (NC). Course is repeatable.

EE 260. Seminar in Electrical Engineering. (4)

Seminar, four hours. Prerequisite(s): consent of instructor. Seminar on current research topics in electrical engineering, including areas such as signal processing, image processing, control, robotics, intelligent systems, computer vision, and pattern recognition. Course is repeatable to maximum of 16 units.

EE 290. Directed Studies. (1-6)

Individual study, three to eighteen hours. Prerequisite(s): graduate standing; consent of instructor and Graduate Advisor. Individual study, directed by a faculty member, of selected topics in electrical engineering. Graded Satisfactory (S) or No Credit (NC). Course is repeatable to a maximum of 12 units.

EE 297. Directed Research. (1-6)

Outside research, three to eighteen hours. Prerequisite(s): graduate standing; consent of instructor. Research conducted under the supervision of a faculty member on selected problems in electrical engineering. Graded Satisfactory (S) or No Credit (NC). Course is repeatable.

EE 299. Research for the Thesis or Dissertation. (1-12)

Outside research, three to thirty-six hours. Prerequisite(s): graduate standing; consent of instructor. Research in electrical engineering for the M.S. thesis or Ph.D. dissertation. Graded Satisfactory (S) or No Credit (NC). Course is repeatable.