100/EECS 100. Introduction to Computing Systems. (4). (Excl). (BS).
This course will cover how a computer works, from the machine-level to high-level programming. Circuits, instructions, memory, data. Assembly language. Binary arithmetic, data types, data structures. Translation of high level languages. The C programming language: data structures, control, iteration, recursion. Basic algorithm analysis. Students are urged to be waitlisted. Explanation for resolution of the waitlist is given at the first lecture. Students not attending the first laboratory session are assumed to have dropped the course.
181/EECS 181. Introduction to Computer Systems. Credit is granted for only one course among CS 181, Engin. 103, and Engin. 104. (4). (Excl). (BS).
This is an introductory course for students who desire a good working knowledge of basic programming techniques using a high-level language. The course is suitable for non-concentrators in Computer Science and Computer Engineering. Introduction to a high-level programming language, top-down analysis, and structured programming. Basic searching and sorting techniques. No previous experience in computing or programming is assumed. Students will write and debug several computer programs.
183/EECS 183. Elementary Programming Concepts. This course is not intended for computer science concentrators or computer engineering concentrators. (4). (NS). (BS).
This is an introductory course for students who desire a good working knowledge of basic programming techniques using a high-level language. The course is suitable for both non-concentrators and pre-concentrators in Computer Science and Computer Engineering. Suggested as a prerequisite for CS 280 for students whose programming background is not strong. Introduction to a high-level programming language, top-down analysis, and structured programming. Basic searching and sorting techniques. No previous experience in computing or programming is assumed. Students will write and debug several computer programs.
210/EECS 210. Electrical Engineering I. Math. 116. (4). (Excl). (BS).
Introductory electrial engineering topics: audio signals and their processing; basics of electricity; elementary circuit design and analysis. Frequency content of signals, Fourier series, filtering. Analysis of resistive circuits. Steady-state response of circuits of resistors, capacitors, inductors and operational amplifiers to sinusoidal signals (frequency response). Laboratory experience with electrical signals and circuits.
Section 002. This lecture/laboratory course is an introduction to analog electrical systems with particular emphasis on audio circuit and signals. Audio will serve as a unifying and motivating theme for the analyses introduced to students in this course. Time and frequency domain representations. Kirchoff voltage law (KVL) and and Kirchoff current law (KCL) equationa and their applications in circuit analysis. Resistive, reactive (inductors and capacitors), and active (operational amplifiers or op-amps) circuit elements are introduced. Application of op-amps in audio circuits will be emphasized in lecture and laboratory. Sinusoidal and phasor analysis of time-invariant electrical circuits and systems. Power transfer and dissipation. Introduction to Fourier series. RLC circuits and basic filter networks. Laboratory experiments on audio amplifiers, distortion, intermodulation products, low-level differential amplifiers, bass/treble filters. Evaluation: Weekly homework, two Mid-terms and a Final Exam. Laboratory has similar grading structure. Textbook: Schwartz and Oldham, Electrical Engineering: An Introduction, Oxford, 1993. Methods: Three lectures (MWF) per week and one laboratory section (five experiments, almost every other week). Real-life handouts are discussed (1 hour extra lecture during weeks where no laboratory is scheduled). (Ebbini)
270/EECS 270. Introduction to Logic Design. CS 100. (4). (Excl). (BS).
Binary and non-binary systems, Boolean algebra digital design techniques, logic gates, logic minimization, standard combinational circuits, sequential circuits, flip-flops, synthesis of synchronous sequential circuits, PLA's, ROM's, RAM's, arithmetic circuits, computer-aided design. Laboratory includes hardware design and CAD experiments.
280/EECS 280. Programming and Introductory Data Structures. Math. 115 and CS 100. Two credits granted to those who have completed CS 283. (4). (NS). (BS).
Techniques and algorithm development and effective programming, top-down analysis, structured programming, testing, and program correctness. Program language syntax and static runtime semantics. Scope, procedure instantiation, recursion, abstract data types, and parameter passing methods. Structured data types, pointers, linked data structures, stacks, queues, arrays, records, and trees.
284/EECS 284. Introduction to a Programming Language
or System. Some programming knowledge is required.
No credit granted for the C minicourse to those students who have
completed CS 280. (1). (Excl). (BS).
Section 001 – C Language. This course is for students who already know how to program in some language other than C. It is a 14-lecture mini-course which will focus on covering the fundamentals of the C language. Topics will range from basic C control structures (if, switch, while, do while, for, and functions) through the use of basic data structures such as arrays, strings, structures, pointers, and linked lists. We will cover as many of the standard C library functions as possible.
303/EECS 303. Discrete Structures. Math. 115. (4). (Excl). (BS).
Fundamental concepts of algebra; partially ordered sets, lattices, Boolean algebras, semi-groups, rings, polynomial rings. Graphical representation of algebraic systems; graphs, directed graphs. Application of these concepts to various areas of computer science and engineering.
370/EECS 370. Introduction to Computer Organization. CS 270 and CS 280. (4). (Excl). (BS).
Computer organization will be presented as a hierarchy of virtual machines representing the different abstractions from which computers can be viewed. These include the logic level, microprogramming level, and assembly language level. Lab experiments will explore the design of a micro-programmed computer.
380/EECS 380. Data Structures and Algorithms. CS 280 and CS 303. (4). (NS). (BS).
Abstract data types. Recurrence relations and recursions. Advanced data structures: sparse matrices, generalized lists, strings. Tree-searching algorithms, graph algorithms, general searching and sorting. Dynamic storage management. Analysis of algorithms and 0-notation. Complexity. Top-down program development: design, implementation testing, modularity. Several programming assignments.
398/EECS 398. Special Topics. Permission of instructor. (1-4). (Excl).
Topics of current interest selected by the faculty.
400/EECS 400/Math. 419. Linear Spaces and Matrix Theory. Four terms of college mathematics beyond Math. 110. No credit granted to those who have completed or are enrolled in Math. 217 or Math. 513. One credit granted to those who have completed Math. 417. (3). (Excl). (BS).
See Mathematics 419.
426/EECS 426. Fundamentals of Electronic Computer-Aided Design. CS 280 and senior standing. (3). (Excl). (BS).
Course will address, in roughly equal proportion: (1) modeling, simulation, and verification at various abstraction levels; (2) behavioral and logic synthesis; and (3) placement and routing. Emphasis will be on understanding the underlying techniques and algorithms of these various CAD areas rather than on the use of specific CAD tools.
442/EECS 442. Computer Vision. CS 303 and CS 380. (3). (Excl). (BS).
Computational methods for the recovery, representation, and application of visual information. Topics from image formation, binary images, digital geometry, similarity and dissimilarity detection, matching, curve and surface fitting, constraint propagation and relaxation labeling, stereo, shading, texture, object representation and recognition, dynamic scene analysis, and knowledge based techniques. Hardware/software techniques.
470/EECS 470. Computer Architecture. CS 370. (4). (Excl). (BS).
Basic concepts of computer architecture and organization. Computer evolution. Design methodology. Performance evaluation. Elementary queuing models. CPU architecture. Introductions sets. ALU design. Hardwared and microprogrammed control. Nanoprogramming. Memory hierarchies. Virtual memory. Cache design. Input-output architectures. Interrupts and DMA. I/O processors. Parallel processing. Pipelined processors. Multiprocessors.
476/EECS 476. Foundations of Computer Science. CS 280 and 303 or equivalent. (4). (Excl). (BS).
An introduction to computation theory: finite automata, regular languages, pushdown automata, context-free languages. Turing machines, recursive languages and functions, and computational complexity.
477/EECS 477. Introduction to Algorithms. CS 380. (3). (Excl). (BS).
Fundamental techniques for designing efficient algorithms and basic mathematical methods for analyzing their performance. Paradigms for algorithm design: divide-and-conquer, greedy methods, graph search techniques, dynamic programming. Design of efficient data structures and analysis of the running time and space requirements of algorithms in the worst and average cases.
478/EECS 478. Switching and Sequential Systems. CS 270 and CS 303, and senior or graduate standing. (3). (Excl). (BS).
An introduction to the theory of switching networks and sequential systems. Switching functions and realizations, threshold logic, fault detection, connectedness and distinguishability, equivalence and minimality, state identification, system decomposition. (Papaefthymiou)
481/EECS 481. Software Engineering. CS 380. (4). (Excl). (BS).
Pragmatic aspects of the production of software systems, dealing with structuring principles, design methodologies and informal analysis. Emphasis is given to development of large, complex software systems. A term project is usually required. WL:1
482/EECS 482. Introduction to Operating Systems. CS 370 and 380. (4). (Excl). (BS).
Operating system functions and implementations: multitasking; concurrency and synchronization; deadlock; scheduling; resource allocation; real and virtual memory management; input/output; file systems. Students write several substantial programs dealing with concurrency and synchronization in a multitask environment.
483/EECS 483. Compiler Construction. CS 380 and 476. (4). (Excl). (BS).
Introduction to compiling techniques including parsing algorithms, semantic processing, and optimization. Students implement a compiler for a substantial programming language using a compiler generating system.
484/EECS 484/IOE 484. Database Management Systems. CS 380 or IOE 373. (3). (Excl). (BS).
Concepts and methods for the design, creation, query, and management of large enterprise databases. Functions and characteristics of the leading database management systems. Query languages such as SQL, forms, embedded SQL, and application development tools. Database design, normalization, access methods, query optimization, transaction management and concurrency control, recovery, and integrity.
486/EECS 486. Object-Based Software Development. CS 380. (3). (Excl). (BS).
Object-based programming concepts such as data and program abstraction, decomposition of large systems into reusable objects, and inheritance. Programming projects will be done in an object-based language such as Ada. Comparative studies will be made of languages such as C++, Objective C, Eiffel, and Smalltalk that support object-based programming.
487/EECS 487/IOE 478. Interactive Computer Graphics. CS 380 or IOE 373, and senior standing. (3). (Excl). (BS).
Graphics devices and fundamentals of operation. Two dimensional and three dimensional transformations. Interactive graphical techniques and applications. Three dimensional graphics, perspective transformation, hidden line elimination. Data structures and languages for graphics. Interactive graphical programming.
492/EECS 492. Introduction to Artificial Intelligence. CS 380. (4). (Excl). (BS).
Basic artificial intelligence methods using LISP. Topics covered include search, rule-based systems, logic, constraint satisfaction, and knowledge representation.
500. Special Study. Graduate or undergraduate
concentration in Computer Science; and permission of instructor.
(1-6). (Excl). (INDEPENDENT). May be repeated for credit.
Tutorial Lecture Series in System Science. Prerequisite: Graduate standing. Students are introduced to the frontiers of System Science research. The tutorials are delivered by leaders of the respective research fields, invited from academia and industry. The presentations are self-contained and accessible to all graduate students in System Science.
Section 001 – Communications.
Section 002 – Control.
Section 003 – Signal Processing.
505/EECS 505/Math. 562/Aero. 577/IOE 511. Continuous Optimization Methods. Math. 217, 417 or 419. (3). (Excl). (BS).
See Mathematics 562.
543/EECS 543. Knowledge-Based Systems. CS 492 and permission of instructor. (3). (Excl). (BS).
Techniques and principles for developing application software based on explicit representation and manipulation of domain knowledge, as applied to computer vision, robotic control, design and manufacturing, diagnostics, autonomous systems, etc. Topics include: identifying and representing knowledge, integrating knowledge-based behavior into complex systems, reasoning, and handling uncertainty and unpredictability.
571/EECS 571. Principles of Real-Time Computing. CS 470 and CS 482 or permission of instructor. (3). (Excl). (BS).
Principles of real-time computing based on high performance, ultra reliability and environmental interface. Architectures, algorithms, operating systems and applications that deal with time as the most important resource. Real-time scheduling, communications and performance evaluation.
574/EECS 574. Theoretical Computer Science I. CS 476. (4). (Excl). (BS).
Formal grammars, recursive functions, logic, complexity theory.
598/EECS 598. Special Topics in Electrical Engineering and Computer Science. Permission of instructor or advisor. (1-4). (Excl). (BS). May be repeated for credit.
Topics of current interest in electrical engineering and computer science. Lectures, seminar, or laboratory. Can be taken more than once for credit.
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