Course List - Spring 2010

Programming skills for problem solving; programming in C; elementary data structures; asymptotic analysis. Three lecture hours and one recitation hour a week for one semester. Prerequisite: Electrical Engineering 306 or Biomedical Engineering 303 with a grade of at least C.

Representation of signals and systems; system properties; sampling; Laplace and z-transforms; transfer functions and frequency response; convolution; stability; Fourier series; Fourier transform; AM/FM modulation; applications. Prerequisite: Electrical Engineering 411, 331, or Biomedical Engineering 311 with a grade of at least C; and Mathematics 427K with a grade of at least C.

Boolean algebra; analysis and synthesis of combinational and sequential switching networks; applications to computer design. Prerequisite: Electrical Engineering 306 or Computer Sciences 307 with a grade of at least C; and credit with a grade of at least C or registration for Electrical Engineering 312 or Computer Sciences 310.

Basic computer structure; instruction set; addressing modes; assembly language programming; subroutines; arithmetic operations; programming in C; C functions; basic data structures; input/output; and survey of several microcontrollers. Three lecture hours and one laboratory hour a week for one semester. Prerequisite: Electrical Engineering 306 or Biomedical Engineering 303 with a grade of at least C, and Electrical Engineering 312 with a grade of at least C.

Introduction to electrostatics and magnetostatics; properties of conductive, dielectric, and magnetic materials; solutions of Maxwell's equations; uniform plane wave applications; frequency- and time-domain analyses of transmission lines. Prerequisite: Physics 303L and 103N and Mathematics 427K with a grade of at least C in each.

Not open to electrical engineering majors. Brief theory of direct and alternating current circuits; single-phase and three-phase power transmission; electronic devices and instrumentation; electromechanics. Prerequisite: Mathematics 408D, Physics 303L, and 103N with a grade of at least C in each.

Advanced engineering communication skills, with emphasis on technical documents, oral reports, and graphics; collaborative work involving online communication and research. Prerequisite: English 316K with a grade of at least C.

Electronic devices in analog and digital circuits. Device physics and modeling; two-port networks; analysis and design of power supply circuits and amplifiers; frequency response; Bode plots. Laboratory work covers generation and acquisition of test signals; current, voltage, and impedance measurements; transfer function measurement; and spectrum measurements and analysis. Three lecture hours and three laboratory hours a week for one semester. Prerequisite: Credit with a grade of at least C or registration for Electrical Engineering 313 or Biomedical Engineering 343.

Quantum theory of energy levels; semiconductor materials and carrier transport; p-n junctions and Schottky barriers; bipolar and field effect transistors; light-emitting diodes, lasers, and photodetectors. Prerequisite: Mathematics 427K and Physics 303L and 103N with a grade of at least C in each.

Microprocessor organization and interfacing; memory interfacing; hardware-software design of microprocessor systems; applications, including communication systems. Two lecture hours and six laboratory hours a week for one semester. Prerequisite: Electrical Engineering 319K, 322C, and 438 with a grade of at least C in each; and credit with a grade of at least C or registration for Aerospace Engineering 333T, Biomedical Engineering 333T, Chemical Engineering 333T, Civil Engineering 333T, Electrical Engineering 333T, Mechanical Engineering 333T, or Petroleum and Geosystems Engineering 333T.

Embedded microcomputer systems; implementation of multitasking, synchronization, protection, and paging; operating systems for embedded microcomputers; design, optimization, evaluation, and simulation of digital and analog interfaces; real-time microcomputer software; applications, including data acquisition and control. Three lecture hours and three laboratory hours a week for one semester. Prerequisite: Electrical Engineering 345L or 345S with a grade of at least C; and credit with a grade of at least C or registration for Aerospace Engineering 333T, Biomedical Engineering 333T, Chemical Engineering 333T, Civil Engineering 333T, Electrical Engineering 333T, Mechanical Engineering 333T, or Petroleum and Geosystems Engineering 333T.

Architectures of programmable digital signal processors; programming for real-time performance; design and implementation of digital filters, modulators, data scramblers, pulse shapers, and modems in real time; interfaces to telecommunications systems. Three lecture hours and three laboratory hours a week for one semester. Prerequisite: Electrical Engineering 319K and 438 with a grade of at least C in each; credit with a grade of at least C or registration for Aerospace Engineering 333T, Biomedical Engineering 333T, Chemical Engineering 333T, Civil Engineering 333T, Electrical Engineering 333T, Mechanical Engineering 333T, or Petroleum and Geosystems Engineering 333T; and credit with a grade of at least C or registration for Biomedical Engineering 335 or Electrical Engineering 351K.

Modern optical wave phenomena with applications to imaging, holography, fiber optics, lasers, and optical information processing. Prerequisite: Electrical Engineering 313 and 325 with a grade of at least C in each, or Biomedical Engineering 343 with a grade of at least C.

Analysis of linear automatic control systems in time and frequency domains; stability analysis; state variable analysis of continuous-time and discrete-time systems; root locus; Nyquist diagrams; Bode plots; sensitivity; lead and lag compensation. Prerequisite: Electrical Engineering 438 and Mathematics 340L with a grade of at least C in each.

Design principles in microwave and radio frequency systems; transmission lines and waveguides; S-parameter representation; impedance matching; microwave network analysis; microwave devices and components; electromagnetic effects in high-speed/high-frequency applications. Prerequisite: Electrical Engineering 325 with a grade of at least C.

Business organization; discounted cash flow calculations, including present-worth and rate-of-return calculations; replacement analyses; financial analyses; accounting and depreciation; income taxes; inflation; risk analysis, utility theory, decision models, sequential decision making; value of information. Prerequisite: Credit or registration for Electrical Engineering 351K.

Fundamentals of risk management, including portfolio theory, capital asset pricing theory, and effects of financing; hedging risks using forwards, futures, options, and other derivatives; stochastic models of price behavior. Prerequisite: Electrical Engineering 366 with a grade of at least C.

May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

Topic 5: Engineering Programming Languages: Higher-level languages for engineering design and problem solving; object-oriented programming in C++ and UNIX systems programming.

Topic 6: Operating Systems Input/output systems calls, drivers and descriptors, and integrated circuits. Design and implementation of hardware and software for a UNIX-like operating system.

Topic 7: Introduction to Pattern Recognition and Computer Vision: Pattern recognition topics, including Bayesian decision theory, maximum likelihood and estimation, nonparametric techniques, and linear discriminant functions. Computer vision topics, including geometric camera models and calibration, geometry of multiple views and stereopsis, structure from motion, and tracking. Emphasis varies each semester.

Topic 8: Computer Vision Systems: Discussion of current research results and exploration of new directions in computer vision systems. Includes linear discriminant functions, nonmetric methods, unsupervised learning and clustering, model-based vision, segmentation using probabilistic methods, and content-based image and video analysis. Application of the techniques to real-world vision systems. Emphasis varies each semester.

Topic 9: Artificial Neural Systems: Feed-forward networks, distributed associative memory, recurrent networks, self-organization, parallel implementation, and applications.

Topic 10: Data Mining: Analyzing large data sets for interesting and useful information. Includes online analytical processing, finding association rules, clustering, classification, and function approximations. Scalability of algorithms and real-life applications.

Topic 11: Mining the Web: Analysis of data and information available from the World Wide Web. Exploiting the hyperlink structure of the Web for developing better search engines. Content analysis, information retrieval, clustering, and hierarchical categorization of Web documents. Web usage mining. Collaborative filtering and personalizing the Web. Additional prerequisite: Electrical Engineering 380L (Topic 10: Data Mining) or Computer Sciences 391L.

May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

Topic 1: VLSI Testing: Hardware and software reliability analysis of digital systems; testing, design for testability, self-diagnosis, fault-tolerant logic design, error-detecting and error-correcting codes.

Topic 2: Dependable Computing: Design techniques for reliable, fault-tolerant, fail-safe and fail-soft systems; fault diagnosis and fault avoidance methods at program and system levels; experimental and commercial fault-tolerant computer systems.

Topic 4: Digital Systems Simulation: Uses and limitations of simulation algorithms for digital circuits and systems.

Topic 7: VLSI I: CMOS technology; structured digital circuits; VLSI systems; computer-aided design tools and theory for design automation; chip design.

Topic 8: VLSI II: Microelectronic systems architecture; VLSI circuit testing methods; integration of heterogeneous computer-aided design tools; wafer scale integration; advanced high-speed circuit design and integration.

Topic 9: Simulation Methods in CAD/VLSI: Techniques and algorithms for simulating large-scale digital and analog circuits.

Topic 10: Synthesis of Digital Systems: Automatic generation of gate-level implementations from HDL specifications; optimization of two-level, multilevel, and sequential circuits for area, speed, and testability.

Topic 11: Verification of Digital Systems: Automatic verification of digital systems; formal models and specifications, equivalence checking, design verification, temporal logic, BDDs, logical foundations, automata theory, recent developments.

Topic 12: System Design Metrics: Analysis of design at chip, board, and system levels; life cycle implications of design decisions, including design for testability effects on production and field service; economic and customer-driven factors.

Topic 13: Analysis and Design of Digital Integrated Circuits:

Topic 14: Analog Integrated Circuit Design:

Topic 15: Computer Performance Evaluation and Benchmarking: Performance metrics, benchmarks, measurement tools and techniques, simulation, trace generation, sampling, analytical modeling, workload characterization, statistical methods to compare alternatives, linear regression, and design of experiments.

Topic 16: Application-Specific Processing:

Topic 17: High-Level Synthesis of Digital Systems:

Topic 18: Java Processing: The Java run-time environment, Java Virtual Machine, processing Java in interpreted and JIT compilation modes, Java processors, Java benchmarks, characterization of Java workloads, performance impact of Java, optimizing microprocessors for Java.

Topic 19: Mixed-Signal System Design and Modeling:

May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

Topic 1: Acoustics I: Same as Mechanical Engineering 384N (Topic 1: Acoustics). Plane waves in fluids; transient and steady-state reflection and transmission; lumped elements; refraction; strings, membranes, and rooms; horns; ray acoustics; absorption and dispersion.

Topic 2: Acoustics II: Same as Mechanical Engineering 384N (Topic 2: Acoustics II). Rigorous derivation of acoustic wave equation; spherical and cylindrical waves; source theory; vibrating piston; enclosures; waveguides; arrays; diffraction. Additional prerequisite: Electrical Engineering 384N (Topic 1) or Mechanical Engineering 384N (Topic 1: Acoustics I).

Topic 3: Electromechanical Transducers: Same as Mechanical Engineering 384N (Topic 3: Electromechanical Transducers). Electrical, mechanical, and acoustical dynamics; principles of energy conversion, transducer laws, and representation; effects of the transducer characteristics on accuracy and efficiency of energy transformation. Biomedical Engineering 384N (Topic 3: Electromechanical Sensors/Actuators) and Electrical Engineering 384N (Topic 3) may not both be counted.

Topic 4: Nonlinear Acoustics: Same as Mechnical Engineering 384N (Topic 4: Nonlinear Acoustics). Distortion and shock formation in finite amplitude waves; harmonic generation and spectral interactions; absorption and dispersion; radiation pressure; acoustic streaming; weak shock theory; numerical modeling; diffraction of intense sound beams; parametric arrays.

Topic 5: Underwater Acoustics: Same as Mechanical Engineering 384N (Topic 5: Underwater Acoustics). Acoustical properties of the ocean; point sources and Green's functions; reflection phenomena; ray theory; normal mode theory; guided waves in horizontally stratified fluid media; WKB and parabolic approximations. Additional prerequisite: Electrical Engineering 384N (Topic 1), Mechanical Engineering 384N (Topic 1: Acoustics I), or consent of instructor.

Topic 6: Noise Control: Same as Mechanical Engineering 384N (Topic 6: Noise Control). Acoustic modeling techniques; panel radiation theory; absorption, barrier, and enclosure design; diagnosis based on experimental data.

Topic 7: Ultrasonics: Same as Mechanical Engineering 384N (Topic 7: Ultrasonics). Acoustic wave propagation in liquids and solids and at interfaces; transducers, arrays; imaging and sonar systems. Biomedical Engineering 384N (Topic 7: Ultrasonics) and Electrical Engineering 384N (Topic 7) may not both be counted.

Same as Mechanical Engineering 394J. May be repeated for credit when the topics vary. Prerequisite: Graduate standing in engineering and consent of instructor.

Topic 1: Power System Engineering I: Physical features, operational characteristics, and analytical models for major electric power systems and components.

Topic 2: Power System Engineering II: Advanced techniques for solving large power networks; loadflow, symmetrical components, short circuit analysis.

Topic 3: Economic Analysis of Power Systems: Energy resources, cost characteristics of electricity supply, electricity consumption and supply patterns, and impact of regulatory policy.

Topic 4: Environmental Engineering and Energy Systems: Environmental effects and controls for air, water, and land pollution for power systems.

Topic 5: Power System Planning and Practices: The economics of integrated resource planning.

Topic 6: Energy Conversion Engineering: Thermal analysis and operating characteristics of systems for electric power generation.

Topic 7: Power System Harmonics: The study of nonsinusoidal voltages and currents in power systems. Detailed modeling and simulation of harmonics sources, system response, and effects on equipment.