Course Descriptions

Graphs and subgraphs, trees and treelike graphs, planar graphs, connectivity and edge-connectivity, applications. Pre: MATH 311 or consent.

Design and evaluation of machine representations, techniques and algorithms for sorting, pattern processing, computational geometry, mathematical computations, and engineering applications. Introduction to computational issues of time, space, communication, and program correctness. Pre: 367 or consent.

LISP for machine intelligence applications, or related constraint object and logic-oriented languages. Pre: 467 or knowledge of LISP/PROLOG.

Theory, methods and practical applications of autonomous agent systems, including common applications of both software and hardware (robotic) agents. In-depth practical experience with autonomous agents through programming assignments and projects. Pre: 467 or ICS 313 (or equivalent), graduate standing; or consent. (Once a year) (Cross-listed as ICS 606)

Network algorithms, protocols, and packet switching systems for the internet including TCP/IP, routing algorithms, transmission scheduling, link management, buffer management, and simple network management. Pre: 367 or consent.

Propagation of signals in fibers, components, modulation and demodulation, transmission system engineering, network systems and architectures, network design, control and management and packet switching. Pre: 342, 367, and 371; or consent.

Basic security theory, current practices, and emerging research issues. First covering the fundamentals of computer and network security, then will work on research projects on computer and network security

An advanced course in digital processing. Topics include fast DFT algorithms, multirate systems and filter banks, power spectrum estimation, linear prediction, optimum linear filters, and adaptive filtering. A-F only. Open to nonmajors for CR/NC only. Pre: 415 or 640, or consent.

Human visual perception, image formation, sampling and quantization, enhancement and restoration, color image processing, wavelets and multiresolution representations, image and video compression. Pre: 415 or equivalent.

Algorithms for linear, nonlinear, and convex optimization. Emphasis is on methodology and the underlying mathematical structures. Topics include simplex method, network flow methods, optimality conditions, duality, Newton’s method and interior point methods. EE, ME, MIS and MATH majors only. Pre: MATH 311 or consent. (Alt. years)

Sequential decision-making via dynamic programming. Optimal control of stochastic dynamic systems. Applications in linear-quadratic control, inventory control, resource allocation, scheduling, and control of queues. Rollout and other suboptimal methods. Value and policy iteration. Pre: 342 or MATH 371 or MATH 471, or consent.

Electronic circuits for precision measurement, computation, and signal processing. Low noise and interference reduction techniques. High-frequency and high-speed techniques. Micro-processor and biomedical applications. Pre: 422.

Advanced physical principles and design of modern solid-state electronic devices. Heterostructures, photodetectors, LED, junction lasers, and other devices of current importance identified from the current literature. A-F only. Pre: 327.

Fundamentals of optical radiation, including stimulated and spontaneous processes. Optical electronics including optical resonators, lasers, optical detectors, lightguiding, and applications. A-F only. Pre: 327 or consent.

Electro-optics, noise detection, light and sound dielectric waveguide phenomena, lasers, optics, phase conjugation. Pre: 622 or consent.

Technology methods and physical principles of microsensors and microactuators. Vacuum technology, thin film deposition and characterization techniques, solid mechanics, micromachining, acoustics, piezoelectricity and principles of current microtransducers. Pre: 327 or consent.

Hands on experience in designing, fabricating, testing, and iterating according to rapid-prototyping principles. Students learn state-of-the-art equipment for making their designs, software for simulating designs, and working in design teams. EE majors only. Graduate students only. (Spring only)

Recent developments in phenomena and devices of physical electronics. Pre: 327.

Fabrication constraints and design guidelines for integrated circuits. Nonlinear model of integrated circuit transistor. Design and analysis of integrated logic circuits and linear circuits. Pre: 323.

Challenges and solutions for integrating intermittent renewable energy sources into the power system, with a focus on “smart grid” approaches and demand-response. Using linear programming and other modeling techniques to answer policy-relevant questions. Graduate students only. Pre: 435. (Spring only)

Random variables, multivariate distributions, random sequences, stochastic convergence, stationary and nonstationary processes, spectral analysis, KarhunenLoeve expansion, Markov processes, mean square estimation, Kalman filters. Pre: 342 or MATH 471 (or equivalent).

Poisson, Markov, and renewal processes, M/G/1 queue, G/M/1 queue, queueing networks, simulation, and performance evaluation of computer systems and communication networks. EE, ICS, MATH majors only. Pre: 342, 640 (or concurrent), or consent.

Fundamentals of signal detection and estimation theory. Hypothesis testing, parametric and nonparametric detection, sequential detection, parametric estimation, linear estimation, robust detection and estimation, and applications to communication systems. Pre: 640.

Fundamental performance limits, signal detection and estimation, modulation, intersymbol interference, equalization adaptive filtering, sequence detection, synchronization, fading multipath channels, spread spectrum. Pre: 640.

Fundamentals of computer communication networks including modeling, performance evaluation, routing, flow control, local area networks, distributed algorithms, and optimization algorithms. Pre: 342, MATH 471; or consent.

Learning theory, pattern recognition and regression; gradient based algorithms and least square algorithms; Kernel methods; Bayesian learning algorithms; ensemble learning and boosting; principal component analysis; independent component analysis, and clustering; reinforcement learning and approximate dynamic programming. EE, ME, ICS, MATH majors only. Pre: 342.

Measure of information, coding for discrete sources, discrete memoryless channels and capacity, the noisy channel coding theorem, source coding with fidelity criterion, rate-distortion theory, multiuser channels. Pre: 640.

Theory and applications of source coding, rate-distortion theory, companding, lattice coding, tree coding, trellis coding, entropy-constrained coding, asymptotic theory, predictive and differential encoding, combined source/channel coding, vector quantization. Pre: 640.

Linear block codes, soft and hard decision decodings, correction of random errors, cyclic codes, BCH codes, ReedSolomon codes, majority logic decodable codes, burst-error correcting codes, concatenated codes. Pre: MATH 311 or consent.

Convolutional codes, Viterbi algorithm, coded modulation, multistage decoding, concatenated coded modulation, probabilistic decoding, turbo codes, low density parity check codes and iterative decoding. Pre: 648.

State space theory of linear systems, controllability, observability, stability, irreducible realizations. Pre: 452.

Digital simulations, phase-plane analysis, limit cycles and amplitude bounds, Lyapunov’s theorem, circle criterion of stability, lure systems, Popov’s stability theorem. Pre: 650.

Optimal controls introduced through parametric optimization, calculus of variations, Euler-Lagrange and Hamilton-Jacobi equations, Pontryagin’s maximum principle, minimum-time and minimum-fuel problems, dynamic programming, applications. Pre: 650 or consent.

Multivariable frequency response design, signals and systems, linear fractional transformations, LQG Control, Full Information H-infinity Controller Synthesis, H-infinity filtering, model reduction, the four-block problem. Pre: 453 and 650.

Models of computation, high-performance processors, pipelined machines, RISC processors, VLIW, superscalar and fine-grain parallel machines. Data-flow architectures. Hardware/software tradeoffs. CEE, EE, and ME majors only. Pre: 461. (Cross-listed as ICS 660)

Modern operating system software, process communication, distributed systems, device drivers. Software development and maintenance, integration of software packages. Projects reflecting special interests of faculty. Pre: 461 and 468.

Telecommunication-network architecture; switching, broadcast, and wireless networks; protocols, interfaces, routing, flow- and congestion-control techniques; intelligent network architecture; service creation capabilities; multimedia, voice, data, and video networks and services. Pre: 468 or consent.

Solutions of Maxwell’s equations and applications to radiation and propagation of electromagnetic waves. Pre: 372 or consent.

Advanced RF and microwave circuit design for wireless applications. Pre: 473 or consent.

Develop comprehensive understanding of computations techniques for solving engineering electromagnetic problems formulated in terms of integral or differential equations. Eigenvalue problems, radiation, and electromagnetics scattering problems will be discussed and computer programming is required. EE, BE, and CENG majors only. A-F only. Pre: 471 (with a minimum grade of B) or consent. (Spring only)

Systems analysis and electronic instrumentation methods in biomedicine. Network and control-loop modeling, computer simulation, biological transducers, and analysis of electronic and physiological systems. Pre: 326, 326L, and 371; or consent.

Advanced topics in the design of biological detection technologies. Topics include fundamentals of electrochemistry, electrochemical biosensors, DNA and protein biochips, and bioelectronics for bio-signal conditioning and processing. Pre: 324 and 326, or consent. (Once a year)

Design and fabrication of micro- and nanodevices for biomedical applications. Topics include micro- and nanoscale physics, microfluidic physics and microfluidic devices, and micro- and nanoscale fabrication techniques. ENG majors only. A-F only. Pre: 324 or consent. (Fall only

Biomedical signals, digital filters and filter banks, spike train analysis, time-scale and time-frequency representations, nonlinear techniques, Lomb’s algorithm and the Hilbert transform, modeling, Volterra series, Wiener series, Poisson-Wiener series, multichannel data, causality. CE, EE, ME, ICS majors only and any graduate student in JABSOM who has a suitable technical background. Pre: 415 or consent. (Spring only)

Content will reflect special interests of visiting/permanent faculty. (B) artificial intelligence; (C) circuits; (D) communications; (E) computer hardware; (F) computer software; (H) control; (I) devices; (J) fields; (K) power. Repeatable unlimited times. Pre: consent.

Repeatable unlimited times. CR/NC only. Pre: graduate standing and consent.

Research for master’s thesis. Repeatable unlimited times. Pre: candidacy for MS in electrical engineering.

Student assists in classroom instruction under direction and close supervision of faculty member. CR/NC only. Pre: admission to PhD candidacy.

Research for doctoral dissertation. Repeatable unlimited times. Pre: candidacy for PhD in electrical engineering.