Prerequisites: EE 215; graduate standing
Description: Provides an in-depth understanding of adaptive signal processing techniques. Covers Wold decomposition; Yule-Walker equations; spectrum estimation; Weiner filters; linear prediction; Kalman filtering; time-varying system tracking; nonlinear adaptive filtering; and performance analysis of adaptive algorithms and their variations including stochastic gradient, least mean square, least squares, and recursive least squares.