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Course Criteria
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3.00 Credits
Performance and robustness of multivariable systems, linear fractional transformations, LQG/LTR advanced loop shaping, Youla parameterization, H (subscript infinity) optimal control, mixed H (subscript 2) and H (subscript infinity) control, controller synthesis for multiple objective optimal control, linear matrix inequalities theory and case studies. Prerequisite: Elec Eng 431.
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3.00 Credits
An introduction to cluster analysis and clustering algorithms rooted in computational intelligence, computer science and statistics. Clustering in sequential data, massive data and high dimensional data. Students will be evaluated by individual or group research projects and research presentations. Prerequisite: At least one graduate course in statistics, data mining, algorithms, computational intelligence, or neural networks, consistent with student's degree program. (Co-listed with Comp Eng 439, Sys Eng 439, Comp Sci 449 and Stat 439)
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3.00 Credits
Continuation of Elec Eng 341. Effects of discrete noise sources in digital signal processing; discrete spectral analysis of random signals; discrete time signal detection, estimation, and filtering algorithms. Prerequisites: Elec Eng 341 and 343 or 344 or Stat 343.
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3.00 Credits
Introduction to ad hoc and sensor networks, IEEE standards, heterogeneity, quality of service, wireless channel issues, energy awareness, power and topology control, routing, scheduling, rate adaptation, self-organization, admission and flow control, energy harvesting, security and trust levels, hardware and applications. Prerequisite: Comp Eng 348 or Comp Eng 349 or equivalent. (Co-listed with Comp Eng 443 and Sys Eng 443)
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3.00 Credits
Continuous-time stochastic signals, multi-dimensional signals, Wiener and matched filters, LMS equalization, non-linear systems with random inputs, spectral estimation and Markov chains. Prerequisites: Stat 343 or Elec Eng 344.
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3.00 Credits
Classical detection and estimation theory with applications; hypothesis testing, detection of known signals, matched filter receiver implementation, detection of signals with unknown parameters, sequential and nonparametric detection, detection of stochastic signals: Parameter estimation theory with application to modulation. Prerequisite: Elec Eng 344.
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3.00 Credits
Introduction to the principle of wireless communication systems. Topics include: wireless channel characteristics, cellular concepts, channel capacity analysis, transceiver architectures, diversity techniques, multiple access schemes, and practical wireless systems. Prerequisite: Elec Eng 343 or Elec Eng 344 or equivalent.
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3.00 Credits
Principles of information generation, transmission and processing; quantitative measure of information, entropy source encoding; channels; mutual information; channel capacity; Shannon's second theorem for discrete channels; introduction to coding for error controls; continuous information sources. Prerequisites: Elec Eng 343 or Elec Eng 344 or Stat 343.
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3.00 Credits
Advanced topics of current interest in communications and signal processing such as spread spectrum, digital processing of communications, speech, and radar signals, applications of pattern recognition, communications networks, specialized coding topics. Repeatable for additional credit toward degree each time a different subtitle offered. Prerequisite: Elec Eng 343 or 344.
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3.00 Credits
The purpose of this course is to cover selected areas of power electronics in greater depth. The topics covered include small signal analysis of power converters, voltage- and current- mode control, soft switching techniques, power factor correctors, multi-level converters, and PWM techniques. Prerequisite: Elec Eng 353.
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