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Course Criteria
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3.00 Credits
Prereq E E 311 or MSE 302; Stat 360 or 443. Equilibrium statistics of electrons and holes; carrier dynamics; p-n junctions, metal-semiconductor junctions, BJTs, Mosfets, LEDs.
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1.00 - 4.00 Credits
May be repeated for credit. S, F grading.
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3.00 Credits
Prereq E E 489. Dynamic systems from the state variable approach; observability, controllability, stability, and sensitivity of differential and nondifferential systems. Cooperative course taught jointly by WSU and UI (ECE 572).
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3.00 Credits
Prereq E E 501. Optimal linear feedback control, optimal stochastic observers, LQG/LTR design methodology, modern Wiener-Hopf design, robust controllers. Cooperative course taught jointly by WSU and UI (ECE 574).
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3.00 Credits
Prereq E E 501, 507. Introduction and development of computational and analytical methods required to characterize large-scale networks.
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3.00 Credits
Prereq E E 341, 351, Stat 443. Diffraction theory, Fourier transforming and imaging properties of lenses, spatial filtering, holography, temporal and spatial coherence, imaging through random media. Cooperative course taught by WSU, open to UI students (EE 534).
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3.00 Credits
Prereq E E 501. Overview of nonlinear phenomena, Lyapunostability, input-output stability, periodic orbits, singular perturbation, differential geometric methods, bifurcations and complex behaviors.
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3.00 Credits
Prereq Stat 443. Functions of random variables; random sequences; stochastic processes; mean-square stochastic calculus; ergodicity; spectral density; linear transformations, filtering, dynamic systems. Cooperative course taught jointly by WSU and UI (EE 570).
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3.00 Credits
Prereq E E 501, 507, or equivalent. Principles of statistical estimation; LLSE; Kalman filtering; smoothing; prediction; maximum- likelihood and Bayesian estimation.
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3.00 Credits
Prereq E E 501. Model reference adaptive systems (MRAS), adaptive observers, adaptive control, on-line identification, robustness issues, self-tuning regulators.
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