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Course Criteria
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3.00 Credits
Introduction to queuing systems. Network design for centralized and distributed networks. Routing and flow control algorithms. Polling and random access protocols, packet radio, satellite networks, and local area networks.
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3.00 Credits
This course studies the design of robust optimal controllers for linear continuous-time systems. Topics include: normal linear signal/system spaces, matrix fraction descriptions, internal stability, uncertain systems, robust stability, robust performance, SISO/MIMO loopshaping, linear fractional transformations and the generalized regulator problem, H2/H-infinity optimal control, algebraic Riccati equation, and balanced model reductions. (Spring)
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3.00 Credits
Treatment of the basic principles of solids. Topics include periodic structures, lattice waves, electron states, static and dynamic properties of solids, electron-electron interaction transport, and optical properties. (Fall)
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3.00 Credits
This course is an introduction to microwave circuit design and analysis techniques, with particular emphasis on applications for modern microwave communication and sensing systems. An integrated laboratory experience provides exposure to fundamental measurement techniques for device and circuit characterization at microwave frequencies. Students will develop an enhanced understanding of circuit design and analysis principles as applied to modern microwave circuits, as well as become familiar with design techniques for both hand analysis and computer-aided design. An appreciation for basic measurement techniques for characterization of microwave devices, circuits and systems through laboratory experiments will also be developed. Fall.
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3.00 Credits
Fundamentals of probability, random variables, and detection and estimation theory for signal processing, communications, and control. Vector spaces of random variables. Bayesian and Neyman-Pearson hypothesis testing. Bayesian and maximum likelihood estimation. Minimum-variance unbiased estimators and the Cramer-Rao bounds. (Fall)
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3.00 Credits
Optimal control is concerned wth the synthesis of feedback control laws that minimize some specified measure of control system performance. This course is a riorous introduction to the classical theory of optimal control. The topics covered by this course include: 1) the calculus of variations, 2) Pontryagin's principle, 3) dynamic programming, and 4)stochastic dynamic programming.
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3.00 Credits
In-depth analysis of electronic devices with an emphasis on both homojunction and heterojunction devices. Operation of p-n junctions is analyzed, along with BJTs, MOSFETs, and heterojunction devices such as HBTs and MODFETs. (Spring)
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3.00 Credits
A hands-on overview of the important role of photons alongside electrons in modern electrical engineering. Photonics technologies studied include lasers, optical fibers, integrated optics, optical signal processing, holography, optoelectronic devices, and optical modulators. A survey of the properties of light, its interactions with matter, and techniques for generating, guiding, modulating, and detecting coherent laser light.
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3.00 Credits
This course covers essential statistical concepts for communications and signal and image processing. The topics include Bayesian estimation methods such as MMSE and MAP as well as MLE; optimality theory of estimation that includes concepts of sufficiency, consistency, and efficiency; Fisher's information; confidence intervals and basic hypothesis testing; classical Fourier-analysis based spectral analysis methods and modern eigen-decomposition based methods such as MUSIC and ESPRIT; interference suppression for various communication systems including wireless multiuser communications. (Spring)
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3.00 Credits
Fundamentals of random processes, including characterization, convergence issues, covariance and power spectral density. Spectral representations of stochastic processes using Karhunen-Loeve, Fourier, and sampling expansions. Detection and estimation from continueous waveform observations. Other topics: linear prediction and filtering adaptive; Wiener and Kalman filters.
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