Subject: EECS
Term: Fall 2011
EECS 132: Introduction to Programming in Java (600/10287)
MWF 02:00-02:50 PM Aug 29-Dec 09
Connamacher, H
This Lecture and the following Recitations are recommended for Computer Science and Computer Engineering Majors.
EECS 132: Introduction to Programming in Java (610/10288)
M 03:00-03:50 PM Aug 29-Dec 09
Connamacher, H
This Recitation and the following Recitations are recommended for Computer Science and Computer Engineering Majors.
EECS 132: Introduction to Programming in Java (611/10289)
T 09:00-09:50 AM Aug 29-Dec 09
Connamacher, H
This Recitation and the following Recitations are recommended for Computer Science and Computer Engineering Majors.
EECS 132: Introduction to Programming in Java (613/10291)
F 11:30-12:20 PM Aug 29-Dec 09
Connamacher, H
This Recitation and the following Recitations are recommended for Computer Science and Computer Engineering Majors.
EECS 233: Introduction to Data Structures (100/3921)
TR 01:15-02:30 PM Aug 29-Dec 09
Lewicki, M
The programming language Java; pointers, files, and recursion. Representation and manipulation of data: one way and circular linked lists, doubly linked lists; the available space list. Different representations of stacks and queues. Representation of binary trees, trees and graphs. Hashing; searching and sorting. Laboratory. Recommended preparation: ENGR 131.
EECS 246: Signals and Systems (100/3922)
MWF 02:00-02:50 PM Aug 29-Dec 09
Cavusoglu, C
Mechanical Engineering students should take this course in place of EECS 212/214.
EECS 246: Signals and Systems (110/4549)
T 04:30-05:45 PM Aug 29-Dec 09
Cavusoglu, C
The sinusoidal steady state and phasor analysis. Bode plots and their relationship to the frequency domain representation of signals. Gain-bandwidth product, slew-rate and other limitations of real devices. Filter design. Frequency domain considerations including Fourier series and Fourier transforms. Sampling theorem. The Discrete Fourier Transform. The z-transform and digital signal processing. Accompanying laboratory exercises which reinforce classroom lectures. Recommended preparation: ENGR 210 and MATH 224.
EECS 246: Signals and Systems (111/4550)
T 04:30-05:45 PM Aug 29-Dec 09
Cavusoglu, C
The sinusoidal steady state and phasor analysis. Bode plots and their relationship to the frequency domain representation of signals. Gain-bandwidth product, slew-rate and other limitations of real devices. Filter design. Frequency domain considerations including Fourier series and Fourier transforms. Sampling theorem. The Discrete Fourier Transform. The z-transform and digital signal processing. Accompanying laboratory exercises which reinforce classroom lectures. Recommended preparation: ENGR 210 and MATH 224.
EECS 246: Signals and Systems (112/4551)
T 06:00-07:15 PM Aug 29-Dec 09
Cavusoglu, C
The sinusoidal steady state and phasor analysis. Bode plots and their relationship to the frequency domain representation of signals. Gain-bandwidth product, slew-rate and other limitations of real devices. Filter design. Frequency domain considerations including Fourier series and Fourier transforms. Sampling theorem. The Discrete Fourier Transform. The z-transform and digital signal processing. Accompanying laboratory exercises which reinforce classroom lectures. Recommended preparation: ENGR 210 and MATH 224.
EECS 281: Logic Design and Computer Organization (100/3923)
TR 10:00-11:15 AM Aug 29-Dec 09
Branicky, M; Garverick, S
Fundamentals of digital systems in terms of both computer organization and logic level design. Organization of digital computers; information representation; boolean algebra; analysis and synthesis of combinational and sequential circuits; datapaths and register transfers; instruction sets and assembly language; input/output and communication; memory. Recommended preparation: ENGR 131.
EECS 281: Logic Design and Computer Organization (110/4361)
T 01:15-02:05 PM Aug 29-Dec 09
Branicky, M; Garverick, S
Recitation for EECS 281
EECS 281: Logic Design and Computer Organization (111/4362)
W 10:30-11:20 AM Aug 29-Dec 09
Branicky, M; Garverick, S
Recitation for EECS 281
EECS 281: Logic Design and Computer Organization (112/4363)
W 11:30-12:20 PM Aug 29-Dec 09
Branicky, M; Garverick, S
Recitation for EECS 281
EECS 293: Software Craftsmanship (100/10685)
T 10:00-11:15 AM Aug 29-Dec 09
Liberatore, V
A course to improve programming skills, software quality, and the software development process. Software design; Version control; Control issues and routines; Pseudo-code programming process and developer testing; Defensive programming; Classes; Debugging; Self-documenting code; Refactoring.
EECS 293: Software Craftsmanship (110/10686)
W 02:00-03:50 PM Aug 29-Dec 09
Liberatore, V
A course to improve programming skills, software quality, and the software development process. Software design; Version control; Control issues and routines; Pseudo-code programming process and developer testing; Defensive programming; Classes; Debugging; Self-documenting code; Refactoring.
EECS 293: Software Craftsmanship (111/10687)
F 09:30-11:20 AM Aug 29-Dec 09
Liberatore, V
A course to improve programming skills, software quality, and the software development process. Software design; Version control; Control issues and routines; Pseudo-code programming process and developer testing; Defensive programming; Classes; Debugging; Self-documenting code; Refactoring.
EECS 293: Software Craftsmanship (112/10688)
F 02:00-03:50 PM Aug 29-Dec 09
Liberatore, V
A course to improve programming skills, software quality, and the software development process. Software design; Version control; Control issues and routines; Pseudo-code programming process and developer testing; Defensive programming; Classes; Debugging; Self-documenting code; Refactoring.
EECS 301: Digital Logic Laboratory (100/3924)
F 03:00-03:50 PM Aug 29-Dec 09
Bhunia, S
This course is an introductory experimental laboratory for digital networks. The course introduces students to the process of design, analysis, synthesis and implementation of digital networks. The course covers the design of combinational circuits, sequential networks, registers, counters, synchronous/asynchronous Finite State Machines, register based design, and arithmetic computational blocks. Recommended preparation: EECS 281.
EECS 302: Discrete Mathematics (100/4185)
TR 08:30-09:45 AM Aug 29-Dec 09
Connamacher, H
A general introduction to basic mathematical terminology and the techniques of abstract mathematics in the context of discrete mathematics. Topics introduced are mathematical reasoning, Boolean connectives, deduction, mathematical induction, sets, functions and relations, algorithms, graphs, combinatorial reasoning.
Offered as EECS 302 and MATH 304.
EECS 318: VLSI/CAD (100/3925)
TR 10:00-11:15 AM Aug 29-Dec 09
Saab, D
With Very Large Scale Integration (VLSI) technology there is an increased need for Computer-Aided Design (CAD) techniques and tools to help in the design of large digital systems that deliver both performance and functionality. Such high performance tools are of great importance in the VLSI design process, both to perform functional, logical, and behavioral modeling and verification to aid the testing process. This course discusses the fundamentals in behavioral languages, both VHDL and Verilog, with hands-on experience. Recommended preparation: EECS 281, EECS 315.
EECS 322: Integrated Circuits and Electronic Devices (100/3926)
MW 10:00-11:15 AM Aug 29-Dec 09
Zorman, C
Taught together with EECS 415.
EECS 324: Simulation Techniques in Engineering (100/3927)
TR 01:15-02:30 PM Aug 29-Dec 09
Chankong, V
Discrete event systems and simulation concepts. Discrete event simulation with batch and interactive languages. Recommended preparation: Concurrent enrollment in ENGL 398.
EECS 325: Computer Networks I (100/3928)
TR 10:00-11:15 AM Aug 29-Dec 09
Allman, M
Taught together with EECS 425.
EECS 337: Compiler Design (100/3929)
TR 01:15-02:30 PM Aug 29-Dec 09
Oldham, D
Design and implementation of compilers and other language processors. Scanners and lexical analysis; regular expressions and finite automata; scanner generators; parsers and syntax analysis; context free grammars; parser generators; semantic analysis; intermediate code generation; runtime environments; code generation; machine independent optimizations; data flow and dependence analysis. There will be a significant programming project involving the use of compiler tools and software development tools and techniques. Recommended preparation: EECS 233 and EECS 281.
EECS 339: Web Data Mining (101/10323)
MW 03:00-04:15 PM Aug 29-Dec 09
Ozsoyoglu, G
Web crawling technology, web search and information extraction, unsupervised and semi-supervised learning techniques and their application to web data extraction, social network analysis, various pagerank algorithms, link analysis, web resource discovery, web, resource description framework (RDF), XML, Web Ontology Language (OWL). Recommended preparation: EECS 338, EECS 341.
EECS 340: Algorithms and Data Structures (100/3930)
MW 12:30-01:45 PM Aug 29-Dec 09
Koyuturk, M
Efficient sorting algorithms, external sorting methods, internal and external searching, efficient string processing algorithms, geometric and graph algorithms. Recommended preparation: EECS 233 and MATH 304.
EECS 341: Introduction to Database Systems (100/3931)
MWF 02:00-02:50 PM Aug 29-Dec 09
Ozsoyoglu, G
Relational model, ER model, relational algebra and calculus, SQL, OBE, security, views, files and physical database structures, query processing and query optimization, normalization theory, concurrency control, object relational systems, multimedia databases, Oracle SQL server, Microsoft SQL server. Recommended preparation: EECS 233.
EECS 342: Introduction to Global Issues (100/3932)
T 06:00-08:30 PM Aug 29-Dec 09
Sreenath, S
This systems course is based on the paradigm of the world as a complex system. Global issues such as population, world trade and financial markets, resources (energy, water, land), global climate change, and others are considered with particular emphasis put on their mutual interdependence. A reasoning support computer system which contains extensive data and a family of models is used for future assessment. Students are engaged in individual, custom-tailored, projects of creating conditions for a desirable or sustainable future based on data and scientific knowledge available. Students at CWRU will interact with students from fifteen universities that have been strategically selected in order to give global coverage to UNESCO'S Global-problematique Education Network Initiative (GENIe) in joint, participatory scenario analysis via the internet.
EECS 351: Communications and Signal Analysis (100/10040)
MWF 11:30-12:20 PM Aug 29-Dec 09
Buchner, M
Fourier transform analysis and sampling of signals. AM, FM and SSB modulation and other modulation methods such as pulse code, delta, pulse position, PSK and FSK. Detection, multiplexing, performance evaluation in terms of signal-to-noise ratio and bandwidth requirements. Recommended preparation: EECS 246 or equivalent.
EECS 352: Engineering Economics and Decision Analysis (100/3933)
TR 02:45-04:00 PM Aug 29-Dec 09
Chankong, V
Economic analysis of engineering projects, focusing on financial decisions concerning capital investments. Present worth, annual worth, internal rate of return, benefit/cost ratio. Replacement and abandonment policies, effects of taxes, and inflation. Decision making under risk and uncertainty. Decision trees. Value of information.
EECS 359: Bioinformatics in Practice (100/4728)
MW 09:00-10:15 AM Aug 29-Dec 09
Li, J
EECS 359 will meet in the same room as EECS 458.
EECS 360: Manufacturing and Automated Systems (100/10015)
W 05:30-08:00 PM Aug 29-Dec 09
Malakooti, B
Formulation, modeling, planning, and control of manufacturing and automated systems with applications to computer science and engineering problems. Topics include, design of products and processes, location/spatial problems, transportation and assignment, product and process layout, group technology and clustering, cellular and network flow layouts, computer control systems, reliability and maintenance, and statistical quality control. Tools and analysis include: multi-objective optimization, artificial intelligence, and heuristics for combinatorial problems.
Offered as EECS 360 and EECS 460.
EECS 366: Computer Graphics (100/4697)
MW 12:30-01:45 PM Aug 29-Dec 09
Cavusoglu, C
Taught together with EECS 466
EECS 371: Applied Circuit Design (100/4706)
TR 10:00-11:15 AM Aug 29-Dec 09
Sears, L
This course will consist of lectures and lab projects designed to provide students with an opportunity to consolidate their theoretical knowledge of electronics and to acquaint them with the art and practice of circuit and product design. The lectures will cover electrical and electronic circuits and many electronic and electrical devices and applications. Examples include mixed-signal circuits, power electronics, magnetic and piezo components, gas discharge devices, sensors, motors and generators, and power systems. In addition, there will be discussion of professional topics such as regulatory agencies, manufacturing, testing, reliability, and product cost. Weekly labs will be true "design" opportunities representing real-world applications. A specification or functional description will be provided, and the students will design the circuit, select all components, construct a breadboard, and test. The objective will be functional, pragmatic, cost-effective designs.
EECS 374: Advanced Control and Energy Systems (101/10426)
M 05:00-07:30 PM Aug 29-Dec 09
Garcia Sanz, M
This course introduces applied quantitative robust and nonlinear control engineering techniques to regulate automatically renewable energy systems in general and wind turbines in particular. The course also studies the fundamentals for dynamic multidisciplinary modeling and analysis of large multi-megawatt wind turbines (mechanics, aerodynamics, electrical systems, control concepts, etc.). The course combines lecture sessions and lab hours. The 400-level includes an experimental lab competition, where the object is to design, implement, and experimentally validate a control strategy to regulate a real system in the laboratory (helicopter control competition or similar); it will also include additional project design reports.
Offered as EECS 374 and EECS 474.
EECS 374: Advanced Control and Energy Systems (110/10464)
Garcia Sanz, M
This course introduces applied quantitative robust and nonlinear control engineering techniques to regulate automatically renewable energy systems in general and wind turbines in particular. The course also studies the fundamentals for dynamic multidisciplinary modeling and analysis of large multi-megawatt wind turbines (mechanics, aerodynamics, electrical systems, control concepts, etc.). The course combines lecture sessions and lab hours. The 400-level includes an experimental lab competition, where the object is to design, implement, and experimentally validate a control strategy to regulate a real system in the laboratory (helicopter control competition or similar); it will also include additional project design reports.
Offered as EECS 374 and EECS 474.
EECS 390: Advanced Game Development Project (100/3934)
T 08:30-09:45 AM Aug 29-Dec 09, R 08:30-09:45 AM Aug 29-Dec 09
Buchner, M
This game development project course will bring together an interdisciplinary group of advanced undergraduate students in the fields of Electrical Engineering and Computer Science, Art, Music, and English to focus on the design and development of a complete, fully-functioning computer game (as an interdisciplinary team). The student teams are given complete liberty to design their own fully functional games from their original concept to a playable finished product, i.e., from the initial idea through to the wrapped box. The student teams will experience the entire game development cycle as they execute their projects. Responsibilities include creating a game idea, writing a story, developing the artwork, designing characters, implementing music and sound effects, programming and testing the game, and documenting the entire project. Recommended preparation: Junior or Senior standing and consent of instructor.
EECS 393: Software Engineering (100/3944)
MWF 11:30-12:20 PM Aug 29-Dec 09
Podgurski, H
Taught together with EECS 493
EECS 396: Independent Projects (102/10955)
Liberatore, V
Independent projects in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering. Limited to juniors and seniors.
EECS 397: Semantic-Web Biomedicine (113/10299)
R 04:00-06:30 PM Aug 29-Dec 09
Zhang, G
Special topics in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering. Limited to juniors and seniors.
EECS 397: Advanced Game Development Project II (114/10326)
T 08:30-09:45 AM Aug 29-Dec 09, R 08:30-09:45 AM Aug 29-Dec 09
Buchner, M
EECS390 is a pre-requisite
EECS 398: Engineering Projects I (100/3935)
MW 12:30-01:45 PM Aug 29-Dec 09
Schultz, W
Capstone course for electrical, computer and systems and control engineering seniors. Material from previous and concurrent courses used to solve engineering design problems. Professional engineering topics such as project management, engineering design, communications, and professional ethics. Requirements include periodic reporting of progress, plus a final oral presentation and written report. Scheduled formal project presentations during last week of classes. Recommended preparation: Senior standing.
EECS 399: Engineering Projects II (100/3936)
MW 12:30-01:45 PM Aug 29-Dec 09
Schultz, W
Continuation of EECS 398. Material from previous and concurrent courses applied to engineering design and research. Requirements include periodic reporting of progress, plus a final oral presentation and written report. Recommended preparation: EECS 398 or concurrent enrollment.
EECS 400T: Graduate Teaching I (100/3937)
Mohseni, P
EE, CE ANDSY STUDENTS SHOULD REGISTER FOR THIS SECTION.
EECS 400T: Graduate Teaching I (101/3938)
Podgurski, H
CS STUDENTS SHOULD REGISTER FOR THIS SECTION.
EECS 408: Introduction to Linear Systems (100/3939)
T 04:30-07:00 PM Aug 29-Dec 09
Lin, W
Analysis and design of linear feedback systems using state-space techniques. Review of matrix theory, linearization, transition maps and variations of constants formula, structural properties of state-space models, controllability and observability, realization theory, pole assignment and stabilization, linear quadratic regulator problems, observers, and the separation theorem. Recommended preparation: EECS 304.
EECS 415: Integrated Circuit Technology I (100/3940)
MW 10:00-11:15 AM Aug 29-Dec 09
Zorman, C
Taught together with EECS 322.
EECS 419: Computer System Architecture (100/3941)
M 06:00-08:30 PM Aug 29-Dec 09
Papachristou, C
Interaction between computer systems hardware and software. Pipeline techniques - instruction pipelines - arithmetic pipelines. Instruction level parallelism. Cache mechanism. I/O structures. Examples taken from existing computer systems.
EECS 422: Solid State Electronics II (101/10403)
TR 08:30-09:45 AM Aug 29-Dec 09
Feng, P
Advanced physics of semiconductor devices. Review of current transport and semiconductor electronics. Surface and interface properties. P-N junction. Bipolar junction transistors, field effect transistors, solar cells and photonic devices.
EECS 425: Computer Networks I (100/3942)
TR 10:00-11:15 AM Aug 29-Dec 09
Allman, M
Taught together with EECS 325.
EECS 426: MOS Integrated Circuit Design (100/3943)
TR 01:15-02:30 PM Aug 29-Dec 09
Mohseni, P
Design of digital and analog MOS integrated circuits. IC fabrication and device models. Logic, memory, and clock generation. Amplifiers, comparators, references, and switched-capacitor circuits. Characterization of circuit performance with/without parasitics using hand analysis and SPICE circuit simulation. Recommended preparation: EECS 344 and EECS 321.
EECS 433: Database Systems (100/3945)
TR 01:15-02:30 PM Aug 29-Dec 09
Ozsoyoglu, Z
Basic issues in file processing and database management systems. Physical data organization. Relational databases. Database design. Relational Query Languages, SQL. Query languages. Query optimization. Database integrity and security. Object-oriented databases. Object-oriented Query Languages, OQL. Recommended preparation: EECS 341 and MATH 304.
EECS 439: Web Data Mining (101/10324)
MW 03:00-04:15 PM Aug 29-Dec 09
Ozsoyoglu, G
Web crawling technology, web search and information extraction, unsupervised and semi-supervised learning techniques and their application to web data extraction, social network analysis, various pagerank algorithms, link analysis, web resource discovery, web, resource description framework (RDF), XML, Web Ontology Language (OWL). Recommended preparation: EECS 338, EECS 341.
EECS 440: Machine Learning (100/4568)
TR 10:00-11:15 AM Aug 29-Dec 09
Ray, S
Machine learning is a subfield of Artificial Intelligence that is concerned with the design and analysis of algorithms that "learn" and improve with experience, While the broad aim behind research in this area is to build systems that can simulate or even improve on certain aspects of human intelligence, algorithms developed in this area have become very useful in analyzing and predicting the behavior of complex systems. Machine learning algorithms have been used to guide diagnostic systems in medicine, recommend interesting products to customers in e-commerce, play games at human championship levels, and solve many other very complex problems. This course is focused on algorithms for machine learning: their design, analysis and implementation. We will study different learning settings, including supervised, semi-supervised and unsupervised learning. We will study different ways of representing the learning problem, using propositional, multiple-instance and relational representations. We will study the different algorithms that have been developed for these settings, such as decision trees, neural networks, support vector machines, k-means, harmonic functions and Bayesian methods. We will learn about the theoretical tradeoffs in the design of these algorithms, and how to evaluate their behavior in practice. At the end of the course, you should be able to:
--Recognize situations where machine learning algorithms are applicable;
--Understand, represent and formulate the learning problem;
--Apply the appropriate algorithm(s), or if necessary, design your own, with an understanding of the tradeoffs involved;
--Correctly evaluate the behavior of the algorithm when solving the problem.
EECS 452: Random Signals (100/4701)
W 04:15-06:45 PM Aug 29-Dec 09
Loparo, K
Fundamental concepts in probability. Probability distribution and density functions. Random variables, functions of random variables, mean, variance, higher moments, Gaussian random variables, random processes, stationary random processes, and ergodicity. Correlation functions and power spectral density. Orthogonal series representation of colored noise. Representation of bandpass noise and application to communication systems. Application to signals and noise in linear systems. Introduction to estimation, sampling, and prediction. Discussion of Poisson, Gaussian, and Markov processes.
EECS 458: Introduction to Bioinformatics (100/3946)
MW 09:00-10:15 AM Aug 29-Dec 09
Li, J
Fundamental algorithmic methods in computational molecular biology and bioinformatics discussed. Sequence analysis, pairwise and multiple alignment, probabilistic models, phylogenetic analysis, folding and structure prediction emphasized. Recommended preparation: EECS 340, EECS 233.
EECS 460: Manufacturing and Automated Systems (100/10014)
W 05:30-08:00 PM Aug 29-Dec 09
Malakooti, B
Formulation, modeling, planning, and control of manufacturing and automated systems with applications to computer science and engineering problems. Topics include, design of products and processes, location/spatial problems, transportation and assignment, product and process layout, group technology and clustering, cellular and network flow layouts, computer control systems, reliability and maintenance, and statistical quality control. Tools and analysis include: multi-objective optimization, artificial intelligence, and heuristics for combinatorial problems.
Offered as EECS 360 and EECS 460.
EECS 466: Computer Graphics (100/4698)
MW 12:30-01:45 PM Aug 29-Dec 09
Cavusoglu, C
Taught together with EECS 366
EECS 466: Computer Graphics (101/10035)
MW 12:30-01:45 PM Aug 29-Dec 09
Cavusoglu, C
Theory and practice of computer graphics: object and environment representation including coordinate transformations image extraction including perspective, hidden surface, and shading algorithms; and interaction. Covers a wide range of graphic display devices and systems with emphasis in interactive shaded graphics. Laboratory. Recommended preparation: EECS 233.
EECS 474: Advanced Control and Energy Systems (101/10427)
M 05:00-07:30 PM Aug 29-Dec 09
Garcia Sanz, M
This course introduces applied quantitative robust and nonlinear control engineering techniques to regulate automatically renewable energy systems in general and wind turbines in particular. The course also studies the fundamentals for dynamic multidisciplinary modeling and analysis of large multi-megawatt wind turbines (mechanics, aerodynamics, electrical systems, control concepts, etc.). The course combines lecture sessions and lab hours. The 400-level includes an experimental lab competition, where the object is to design, implement, and experimentally validate a control strategy to regulate a real system in the laboratory (helicopter control competition or similar); it will also include additional project design reports.
Offered as EECS 374 and EECS 474.
EECS 474: Advanced Control and Energy Systems (110/10465)
Garcia Sanz, M
This course introduces applied quantitative robust and nonlinear control engineering techniques to regulate automatically renewable energy systems in general and wind turbines in particular. The course also studies the fundamentals for dynamic multidisciplinary modeling and analysis of large multi-megawatt wind turbines (mechanics, aerodynamics, electrical systems, control concepts, etc.). The course combines lecture sessions and lab hours. The 400-level includes an experimental lab competition, where the object is to design, implement, and experimentally validate a control strategy to regulate a real system in the laboratory (helicopter control competition or similar); it will also include additional project design reports.
Offered as EECS 374 and EECS 474.
EECS 480A: Introduction to Wireless Health (100/10553)
T 06:00-08:30 PM Aug 29-Dec 09
Crago, P; Mehregany, M
The class times listed are PST (Pacific Standard Time).
EECS 480B: The Human Body (100/10556)
W 06:00-08:30 PM Aug 29-Dec 09
Crago, P; Mehregany, M
The class times listed are PST (Pacific Standard Time).
EECS 484: Computational Intelligence I: Basic Principles (100/10016)
MW 09:00-10:15 AM Aug 29-Dec 09
Newman, W
This course is concerned with learning the fundamentals of a number of computational methodologies which are used in adaptive parallel distributed information processing. Such methodologies include neural net computing, evolutionary programming, genetic algorithms, fuzzy set theory, and "artificial life." These computational paradigms complement and supplement the traditional practices of pattern recognition and artificial intelligence. Functionalities covered include self-organization, learning a model or supervised learning, optimization, and memorization.
EECS 485: VLSI Systems (100/3947)
W 06:00-08:30 PM Aug 29-Dec 09
Saab, D
Basic MOSFET models, inverters, steering logic, the silicon gate, nMOS process, design rules, basic design structures (e.g., NAND and NOR gates, PLA, ROM, RAM), design methodology and tools (spice, N.mpc, Caesar, mkpla), VLSI technology and system architecture. Requires project and student presentation, laboratory.
EECS 490: Digital Image Processing (100/10017)
TR 04:30-05:45 PM Aug 29-Dec 09
Merat, F
Digital images are introduced as two-dimensional sampled arrays of data. The course begins with one-to-one operations such as image addition and subtraction and image descriptors such as the histogram. Basic filters such as the gradient and Laplacian in the spatial domain are used to enhance images. The 2-D Fourier transform is introduced and frequency domain operations such as high and low-pass filtering are developed. It is shown how filtering techniques can be used to remove noise and other image degradation. The different methods of representing color images are described and fundamental concepts of color image transformations and color image processing are developed. One or more advanced topics such as wavelets, image compression, and pattern recognition will be covered as time permits. Programming assignments using software such as MATLAB will illustrate the application and implementation of digital image processing.
EECS 490: Digital Image Processing (101/10037)
TR 04:30-05:45 PM Aug 29-Dec 09
Merat, F
Digital images are introduced as two-dimensional sampled arrays of data. The course begins with one-to-one operations such as image addition and subtraction and image descriptors such as the histogram. Basic filters such as the gradient and Laplacian in the spatial domain are used to enhance images. The 2-D Fourier transform is introduced and frequency domain operations such as high and low-pass filtering are developed. It is shown how filtering techniques can be used to remove noise and other image degradation. The different methods of representing color images are described and fundamental concepts of color image transformations and color image processing are developed. One or more advanced topics such as wavelets, image compression, and pattern recognition will be covered as time permits. Programming assignments using software such as MATLAB will illustrate the application and implementation of digital image processing.
EECS 491: Artificial Intelligence (100/4575)
TR 04:15-05:30 PM Aug 29-Dec 09
Lewicki, M; Ray, S
This course covers advanced topics in Artificial Intelligence. Topics include representing knowledge using directed and undirected probabilistic graphical models, associated exact and approximate inference algorithms, statistical relational learning, advanced topics in reinforcement learning and automated planning.
EECS 493: Software Engineering (100/4732)
MWF 11:30-12:20 PM Aug 29-Dec 09
Podgurski, H
Taught together with EECS 393
EECS 493: Software Engineering (101/10038)
MWF 11:30-12:20 PM Aug 29-Dec 09
Podgurski, H
Topics: Introduction to software engineering; software lifecycle models; development team organization and project management; requirements analysis and specification techniques; software design techniques; programming practices; software validation techniques; software maintenance practices; software engineering ethics. Undergraduates work in teams to complete a significant software development project. Graduate students are required to complete a research project. Recommended preparation for EECS 493: EECS 337.
Offered as EECS 393 and EECS 493.
EECS 495: Nanometer VLSI Design (100/3948)
TR 04:30-05:45 PM Aug 29-Dec 09
Bhunia, S
Semiconductor industry has evolved rapidly over the past four decades to meet the increasing demand on computing power by continuous miniaturization of devices. Now we are in the nanometer technology regime with the device dimensions scaled below 100nm. VLSI design using nanometer technologies involves some major challenges. This course will explain all the major challenges associated with nanoscale VLSI design such as dynamic and leakage power, parameter variations, reliability and robustness. The course will present modeling and analysis techniques for timing, power and noise in nanometer era. Finally, the course will cover the circuit/architecture level design solutions for low power, high-performance, testable and robust VLSI system. The techniques will be applicable to design of microprocessor, digital signal processor (DSP) as well as application specific integrated circuits (ASIC). The course includes a project which requires the student to work on a nanometer design issue. Recommended preparation: EECS 426 or EECS 485.
EECS 500: EECS Colloquium (100/3949)
TR 11:30-12:30 PM Aug 29-Dec 09
Ray, S
Seminars on current topics in Electrical Engineering and Computer Science.
EECS 500T: Graduate Teaching II (100/3950)
Mohseni, P
EE, CE, AND SY STUDENTS SHOULD REGISTER FOR THIS SECTION.
EECS 500T: Graduate Teaching II (101/3951)
Podgurski, H
CS STUDENTS SHOULD REGISTER FOR THIS SECTION.
EECS 589: Robotics II (101/10301)
TR 02:45-04:00 PM Aug 29-Dec 09
Lee, G
Survey of research issues in robotics. Force control, visual servoing, robot autonomy, on-line planning, high-speed control, man/machine interfaces, robot learning, sensory processing for real-time control. Primarily a project-based lab course in which students design real-time software executing on multi-processors to control an industrial robot. Recommended preparation: EECS 489.
EECS 600: Semantic-Web Biomedicine (103/10304)
R 04:00-06:30 PM Aug 29-Dec 09
Zhang, G
Offered as EECS 600 and SYBB 600.
EECS 600T: Graduate Teaching III (100/3952)
Mohseni, P
EE, CE, AND SY STUDENTS SHOULD REGISTER FOR THIS SECTION.
EECS 600T: Graduate Teaching III (101/3953)
Podgurski, H
CS STUDENTS SHOULD REGISTER FOR THIS SECTION.
EECS 601: Independent Study (100/4679)
Koyuturk, M
EECS 601: Independent Study (102/4756)
Mohseni, P
EECS 601: Independent Study (104/4791)
Liberatore, V
EECS 601: Independent Study (106/10908)
Podgurski, H
EECS 601: Independent Study (107/10909)
Loparo, K
EECS 601: Independent Study (108/10949)
Cavusoglu, C
EECS 601: Independent Study (109/10963)
Garcia Sanz, M
EECS 601: Independent Study (110/10970)
Papachristou, C
EECS 649: Project M.S. (100/3958)
Bhunia, S
M.S. Project for EE Plan B students.
EECS 649: Project M.S. (101/3959)
Branicky, M
EECS 649: Project M.S. (102/3960)
Buchner, M
EECS 649: Project M.S. (103/3961)
Cavusoglu, C
EECS 649: Project M.S. (104/3962)
Chankong, V
EECS 649: Project M.S. (105/3963)
Garverick, S
EECS 649: Project M.S. (107/4311)
Koyuturk, M
EECS 649: Project M.S. (108/4312)
Li, J
EECS 649: Project M.S. (109/4313)
Liberatore, V
EECS 649: Project M.S. (110/4314)
Lin, W
EECS 649: Project M.S. (111/4315)
Loparo, K
EECS 649: Project M.S. (112/4316)
Malakooti, B
EECS 649: Project M.S. (114/4318)
Mehregany, M
EECS 649: Project M.S. (115/4319)
Merat, F
EECS 649: Project M.S. (116/4320)
Mesarovic, M
EECS 649: Project M.S. (117/4321)
Mohseni, P
EECS 649: Project M.S. (118/4322)
Newman, W
EECS 649: Project M.S. (119/4323)
Ozsoyoglu, G
EECS 649: Project M.S. (120/4324)
Ozsoyoglu, Z
EECS 649: Project M.S. (121/4325)
Papachristou, C
EECS 649: Project M.S. (122/4326)
Podgurski, H
EECS 649: Project M.S. (123/4327)
Rabinovich, M
EECS 649: Project M.S. (124/4328)
Saab, D
EECS 649: Project M.S. (125/4329)
Sreenath, S
EECS 649: Project M.S. (126/4330)
Staff
EECS 649: Project M.S. (127/4331)
Tien, N
EECS 649: Project M.S. (129/4333)
Young, D
EECS 649: Project M.S. (130/4334)
Zhang, G
EECS 649: Project M.S. (131/4335)
Zhang, X
EECS 649: Project M.S. (132/4336)
Zorman, C
EECS 651: Thesis M.S. (100/3965)
Bhunia, S
EECS 651: Thesis M.S. (101/3966)
Branicky, M
EECS 651: Thesis M.S. (102/3967)
Buchner, M
EECS 651: Thesis M.S. (103/3968)
Cavusoglu, C
EECS 651: Thesis M.S. (104/3969)
Chankong, V
EECS 651: Thesis M.S. (105/3970)
Garverick, S
EECS 651: Thesis M.S. (107/3972)
Koyuturk, M
EECS 651: Thesis M.S. (108/3973)
Li, J
EECS 651: Thesis M.S. (109/3974)
Liberatore, V
EECS 651: Thesis M.S. (110/3975)
Lin, W
EECS 651: Thesis M.S. (111/3976)
Loparo, K
EECS 651: Thesis M.S. (112/3977)
Malakooti, B
EECS 651: Thesis M.S. (114/3979)
Mehregany, M
EECS 651: Thesis M.S. (115/3980)
Merat, F
EECS 651: Thesis M.S. (116/3981)
Mesarovic, M
EECS 651: Thesis M.S. (117/3982)
Mohseni, P
EECS 651: Thesis M.S. (118/3983)
Newman, W
EECS 651: Thesis M.S. (119/3984)
Ozsoyoglu, G
EECS 651: Thesis M.S. (120/3985)
Ozsoyoglu, Z
EECS 651: Thesis M.S. (121/3986)
Papachristou, C
EECS 651: Thesis M.S. (122/3987)
Podgurski, H
EECS 651: Thesis M.S. (123/3988)
Rabinovich, M
EECS 651: Thesis M.S. (124/3989)
Saab, D
EECS 651: Thesis M.S. (125/3990)
Sreenath, S
EECS 651: Thesis M.S. (126/4337)
Staff
EECS 651: Thesis M.S. (127/4338)
Tien, N
EECS 651: Thesis M.S. (129/4340)
Young, D
EECS 651: Thesis M.S. (130/4341)
Zhang, G
EECS 651: Thesis M.S. (131/4342)
Zhang, X
EECS 651: Thesis M.S. (132/4343)
Zorman, C
EECS 651: Thesis M.S. (134/4593)
Ray, S
EECS 651: Thesis M.S. (135/4649)
Garcia Sanz, M
EECS 651: Thesis M.S. (136/4650)
Lewicki, M
EECS 651: Thesis M.S. (137/4748)
Quinn, R
EECS 651: Thesis M.S. (138/10947)
Griswold, M
EECS 701: Dissertation Ph.D. (100/3991)
Bhunia, S
EECS 701: Dissertation Ph.D. (101/3992)
Branicky, M
EECS 701: Dissertation Ph.D. (102/3993)
Buchner, M
EECS 701: Dissertation Ph.D. (103/3994)
Cavusoglu, C
EECS 701: Dissertation Ph.D. (104/3995)
Chankong, V
EECS 701: Dissertation Ph.D. (105/3996)
Garverick, S
EECS 701: Dissertation Ph.D. (107/3998)
Koyuturk, M
EECS 701: Dissertation Ph.D. (108/3999)
Li, J
EECS 701: Dissertation Ph.D. (109/4000)
Liberatore, V
EECS 701: Dissertation Ph.D. (110/4001)
Lin, W
EECS 701: Dissertation Ph.D. (111/4002)
Loparo, K
EECS 701: Dissertation Ph.D. (112/4003)
Malakooti, B
EECS 701: Dissertation Ph.D. (113/4004)
Quinn, R
EECS 701: Dissertation Ph.D. (114/4005)
Mehregany, M
EECS 701: Dissertation Ph.D. (115/4006)
Merat, F
EECS 701: Dissertation Ph.D. (117/4008)
Mohseni, P
EECS 701: Dissertation Ph.D. (118/4009)
Newman, W
EECS 701: Dissertation Ph.D. (119/4010)
Ozsoyoglu, G
EECS 701: Dissertation Ph.D. (120/4011)
Ozsoyoglu, Z
EECS 701: Dissertation Ph.D. (121/4012)
Papachristou, C
EECS 701: Dissertation Ph.D. (122/4013)
Podgurski, H
EECS 701: Dissertation Ph.D. (123/4014)
Rabinovich, M
EECS 701: Dissertation Ph.D. (124/4015)
Saab, D
EECS 701: Dissertation Ph.D. (125/4016)
Sreenath, S
EECS 701: Dissertation Ph.D. (126/4017)
Staff
EECS 701: Dissertation Ph.D. (127/4018)
Tien, N
EECS 701: Dissertation Ph.D. (128/4019)
Yang, J
EECS 701: Dissertation Ph.D. (129/4307)
Young, D
EECS 701: Dissertation Ph.D. (130/4308)
Zhang, G
EECS 701: Dissertation Ph.D. (131/4309)
Zhang, X
EECS 701: Dissertation Ph.D. (132/4310)
Zorman, C
EECS 701: Dissertation Ph.D. (134/4542)
Ko, W
EECS 701: Dissertation Ph.D. (136/4594)
Ray, S
EECS 701: Dissertation Ph.D. (137/4651)
Garcia Sanz, M
EECS 701: Dissertation Ph.D. (138/4652)
Lewicki, M
EECS 701: Dissertation Ph.D. (139/10738)
Allman, M
EECS 701: Dissertation Ph.D. (140/10739)
Yu, X
EECS 701: Dissertation Ph.D. (141/10889)
Zhao, H
EECS 701: Dissertation Ph.D. (142/10925)
Feng, P