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Course Criteria
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4.00 Credits
This course studies the issues dealing with real-time embedded system design. Topics include: microprocessor architecture, assembly language, real-time programming, space and time limitations, relations between ANSIC Compiler output and assembly language, compiler linkers and using a system development package for C programming. (F,W,S).
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0.00 Credits
This lab course must be taken with its associated ECE 473 Lecture. (F,W,S)
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3.00 Credits
Principles of language compilation. Introduction to formal languages. Lexical analysis, top-down and bottom-up parsing, code generation and optimization. Error handling and symbol table management. Run-time storage management. Programming language design. Introduction to compiler-writing tools. A software design project is required. Three lecture hours per week.
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4.00 Credits
Design methodology, performance analysis using probability and statistic methods, hardwired and microprogramming in CPU design, hardware design languages and memory design. Advanced concepts in computer architecture. A design project is required. Three lecture hours per week and one three-hour laboratory per week.
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3.00 Credits
Advances in computer architecture, parallel structures, performance evaluation, memory bandwidth considerations, processing bandwidth, communication and synchronization. A design project is required. Three lecture hours per week.
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4.00 Credits
Introduction to computer operating systems. Process management, threads, CPU scheduling, memory management, process synchronization, file systems and I/O devices. Selected advanced topics, e.g., distributed systems, deadlock, I/O, job scheduling, and performance analysis using queueing models, will be introduced. Case studies of modern operating systems. A design project is required. Four lecture hours per week.
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3.00 Credits
Basic concepts and methodology of artificial intelligence from a computer engineering perspective. Emphasis is placed on the knowledge representations, reasoning and algorithms for the design and implementation of intelligent systems. Introduction to an AI language and representative intelligence systems. A design project is required. Three lecture hours per week.
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4.00 Credits
Fundamentals of discrete-time signals and systems. Introduction to z-transform and its applications. Design of digital filters. Characteristics of analog-to-digital and digital-to-analog converters. Fourier transform of sequences, DFT and FFT algorithms. An introduction to software tools for the simulation and design of real time-digital filters. Implementation of digital systems using digital signal processing boards. Three hours lecture and three hours laboratory experiments per week.
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0.00 Credits
This lab must be taken concurrently with its associated ECE 480 lecture. (F,W,S)
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4.00 Credits
Applications to machine vision. Representative topics are: optics and lighting, sensor characteristics, image acquisition, image analysis, segmentation, connectivity, shape description, hardware for vision applications, software considerations, applications including automatic inspection and metrology. Open lab and project will be required.
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