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Course Criteria
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3.00 Credits
3 hours lecture Prerequisites: ECE 384, 475; or permission of instructor Representation, analysis and design of discrete signals and systems. Topics include a review of the z-transform and the discrete-time Fourier transform, the fast Fourier transform, digital filter structures, digital filter design techniques, quantization issues and effects of finite word-length arithmetic, sampling and oversampling, decimation and interpolation, linear prediction, the Hilbert transform, and the complex cepstrum. Students gain experience in analyzing and designing digital signal processing systems through computer projects.
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3.00 Credits
3 hours lecture Prerequisites: ECE 521, 597; or permission of instructor Classical theories in detecting and processing both active and passive signals in noise with special emphasis on the underwater environment and associated techniques in sound navigation ranging (SONAR). Both spatial and temporal processing methods are studied including beamforming, matched filtering, effects of noise and interference, application and utility of frequency agile signals, narrow band and broadband passive techniques, and adaptive algorithms to address the time/ space varying interference sources. Applications in underwater detection, classification, localization, and communication are also discussed.
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3.00 Credits
3 hours lecture Prerequisites: Probability and random variables; or permission of instructor An introduction to artificial intelligence and expert systems. Topics covered include state-space representations and search methods; problem-reduction representation and search methods; Bayes networks; theorem proving using predicate calculus; natural languages; expert system design using Lisp or Prolog; and an introduction to neural networks and pattern recognition.
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3.00 Credits
3 hours lecture Prerequisites: ECE 384 or permission of instructor Fundamentals of time series analysis. Topics include: moving average and autoregressive models; estimation of the mean and autocorrelation; statistical forecasting; spectral analysis and estimation; bivariate processes; linear system identification; and non stationary time series. Application to electrical engineering problems is emphasized.
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3.00 Credits
3 hours lecture Prerequisites: Graduate standing Elementary exposition of linear algebra and time domain methods and their utility in the analysis and design of linear systems. Linear space, state variables, controllability, observability, assignability, linear state variable feedback design, time variant systems and adjoint model are included.
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3.00 Credits
3 hours lecture Prerequisites: ECE 581 The calculus of variation and classical optimal control techniques based on it. Modern control theory is presented including Pontryagin’s principle of maximum and Bellman’s dynamic programming. Relation to Hamiltonian mechanics is discussed.
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3.00 Credits
3 hours lecture Prerequisites: ECE 581 Analysis and design techniques for nonlinear systems. Topics covered include singular points, contraction mapping, existence and uniqueness of solutions, comparison principle, Lyapunov stability, stability of perturbed systems, slowly varying systems, input-output stability, circle criterion, Popov criterion, small-gain theorem, describing function method, feedback control design via linearization, exact feedback linearization, and other selected topics from nonlinear control theory.
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3.00 Credits
3 hours lecture Prerequisites: ECE 521, 581 Basic concepts and principles of estimation theory. Topics include least squares estimation, recursive least squares estimation, best linear unbiased estimator, Bayes estimation, maximum likelihood estimation, maximum a posteriori estimation, conditional mean, Gauss-Markov random process, Kalman filtering, prediction, smoothing, and nonlinear estimation. Estimator bounds and properties are discussed.
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3.00 Credits
3 hours lecture Prerequisites: Probability and random variables; or permission of instructor Concepts of fuzzy sets, understanding their impact on mathematics, and development of the principles of design. Crisp sets, their operations, and classical two value logic are reviewed and extended to fuzzy sets and fuzzy logic. Relations, orderings, compatibility maps, and morphisms are extended to their fuzzy counterparts. Fuzzy numbers, fuzzy arithmetic and equations are presented. Approximate reasoning, evidence theory, possibility theory and probability are covered. Measures of uncertainty, vagueness, and information are developed. Application to fuzzy control is presented while applications to other disciplines are studied via individualized student projects.
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3.00 Credits
3 hours lecture Prerequisites: Permission of instructor Topics of timely interest in Electrical and Computer Engineering. Course content may change from year to year according to instructor’s preferences.
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