Instructor:  Clayton Scott

T,Th 9:00 a.m. - 10:30 a.m.

3 cr. hrs.

Principles of estimation, linear filtering and detection.  Estimation:  linear and nonlinear minimum mean squared error estimation, and other strategies.  Linear filtering:  Wiener and Kalman filtering.  Detection:  simple, composite, binary and multiple hypotheses.  Newman-Pearson and Bayesian approaches.

Prerequisite: EECS 501