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Course Criteria
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3.00 Credits
ENG EC 312. The concepts of computer architecture from a quantitative approach. Instruction set design with examples from both RISC and CISC architectures. Processor implementation techniques and microprogramming, pipelining and methods to cope with pipeline hazards, and the memory hierarchy (cache and virtual memory). Parallel and vector architectures, future directions, and examples of highly parallel computers. 4 cr,.
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4.00 Credits
ENG EK 127 or knowledge of general programming language, ENG ME 308 or ENG EC 381. Modeling of discrete event systems and their analysis through simulations. Systems considered include, but are not limited to, manufacturing systems, computer-communication networks, and computer systems. Simulating random environments and output analysis in such contexts. A simulation language is introduced and is the main tool for simulation experimentation. Meets with ENG MN 514; students may not take both for credit. 4 cr.
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4.00 Credits
ENG EC 415 and ENG EC 381 or CAS MA 381. Channel characterization; signal design; optimal receivers; coherent and noncoherent digital signaling; intersymbol interference; baseband shaping; equalization, synchronization, and detection; error detection and correction coding. 4 cr.
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4.00 Credits
ENG EC 416, ENG EC 402, or ENG EC 415. Advanced structures and techniques for digital signal processing and their properties in relation to application requirements such as real-time, low bandwidth, and low-power operation. Optimal FIR filter design; time-dependent Fourier transform and filterbanks; Hilbert transform relations; cepstral analysis and deconvolution; parametric signal modeling; multidimensional signal processing; multirate signal processing. 4 cr.
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3.00 Credits
ENG EC 381 or equivalent. Discrete memory-less stationary sources and channels; information measures on discrete and continuous alphabets and their properties: entropy, conditional entropy, relative entropy, mutual information, differential entropy; elementary constrained convex optimization; fundamental information inequalities: data-processing, and Fano's; block source coding with outage: weak law of large numbers, entropically typical sequences and typical sets, asymptotic equipartition property; block channel coding with and without cost constraints: jointly typical sequences, channel capacity, random coding, Shannon's channel coding theorem, introduction to practical linear block codes; rate-distortion theory: Shannon's block source coding theorem relative to a fidelity criterion; source and channel coding for Gaussian sources and channels and parallel Gaussian sources and channels (water-filling and reverse water-filling); Shannon's source-channel separation theorem for point-to-point communication; Lossless data compression: Kraft's inequality, Shannon's lossless source coding theorem, variable-length source codes including Huffman, Shannon-Fano-Elias, and arithmetic codes; applications; mini-course project. 4
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4.00 Credits
ENG EC 511. Planning and control of a software project. Software project economics. Cost factors and cost estimation models; cost/benefit tradeoffs, risk analysis; project metrics for quality, schedule, budget, and progress. Role of the project manager and organization of the development team. Case studies used to illustrate successes and failures in the management of actual projects. Small-team projects involving the development of software project plans. 4 cr.
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4.00 Credits
ENG EC 381 and ENG EC 416 or equivalents. Review of signals and systems in multiple dimensions. Sampling of still images. Quantization of image intensities. Human visual system. Image color spaces. Image models and transformations. Image enhancement and restoration. Image analysis. Image compression fundamentals. Image compression standards (JPEG, JPEG-2000). Homework will include MATLAB assignments. 4 cr.
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3.00 Credits
Prereq: ENG ME 411. Introduction to optimization problems and algorithms emphasizing problem formulation, basic methodologies, and underlying mathematical structures. Classical optimization theory as well as recent advances in the field. Topics include modeling issues and formulations, simplex method, duality theory, sensitivity analysis, large-scale optimization, integer programming, interior-point methods, nonlinear programming, optimality conditions, gradient methods, and conjugate direction methods. Applications considered; case studies included. Extensive paradigms from production planning and scheduling in manufacturing systems, other illustrative applications include fleet management, air traffic flow management, optimal routing in communication networks, optimal portfolio selection. Meets with ENG MN 524; students may not take both for credit. 4 cr.
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4.00 Credits
CAS MA 124. Selected topics in discrete mathematics: formal systems, mathematical deduction, logical concepts, theorem proving. Sets, relations on sets, operations on sets. Functions, graphs, mathematical structures, morphisms, algebraic structures, semigroups, quotient groups, finite-state machines, their homomorphism, and simulation. Machines as recognizers, regular sets. Kleene theorem. 4 cr.
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4.00 Credits
ENG EC 381 or ENG EK 500. Markov chains, Chapman-Kolmogorov equation. Classification of states, limiting probabilities. Poisson process and its generalization, continuous-time Markov chain, queuing theory, reliability theory. 4 cr.
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