Course List - Spring 2010

Linear circuit elements; nodal and mesh analysis; operational amplifiers; capacitance and inductance; simple transient response; sinusoidal steady state analysis; Bode plots; three-phase circuits; transformers; two-port networks (Z-parameters and Y-parameters); computer-aided analysis and design. Three lecture hours and two recitation hours a week for one semester. Prerequisite: Electrical Engineering 302 or 302H with a grade of at least C; credit with a grade of at least C or registration for Mathematics 427K; and credit with a grade of at least C or registration for Physics 303L and 103N.

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.

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.

Introduction to the engineering design process; assessing engineering problems and customer needs; acquiring, documenting, and verifying requirements; high-level system design principles; effects of economic, environmental, ethical, safety, and social issues in design; writing design specifications. Two lecture hours and three laboratory hours a week for one semester. Prerequisite: Aerospace Engineering 333T, Biomedical Engineering 333T, Chemical Engineering 333T, Civil Engineering 333T, Electrical Engineering 333T, Mechanical Engineering 333T, or Petroleum and Geosystems Engineering 333T, with a grade of at least C; credit with a grade of at least C or registration for Electrical Engineering 321K, 440, 345L, 345S, 362L, 371C, 372L, or 374L; and credit with a grade of at least C or registration for Electrical Engineering 366.

Design and experimental projects done with teams of students from multiple engineering disciplines; the ethics of design for safety and reliability; emphasis on written and oral reporting of engineering projects. Three lecture hours a week for one semester, with additional laboratory hours to be arranged. Prerequisite: Electrical Engineering 364D and 366 with a grade of at least C in each; and Electrical Engineering 321K, 440, 345L, 345S, 362L, 371C, 372L, or 374L 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.