EE 617 Statistical Signal Processing

Mathematical modeling of signal processing; Wiener-Kalman filters, LP, and LMS methods; estimation and detection covering minimum-variance-unbiased (MVUB) and maximum likelihood (ML) estimators, Cramer-Rao bound, Bayes and Neyman- Pearson detectors, and CFAR detectors; methods of least squares (LS): batch mode, weighted LS, total LS (TLS), and recursive LS (RLS); SVD and high resolution spectral estimation methods including MUSIC, modified FBLP, and Min-Norm; higher order spectral analysis (HOSA) with applications of current interest; PDA and JPDA data association trackers with MultiDATTM; and applied computer projects on major topics.

Credits

3

Prerequisite

EE 616

Distribution

Electrical Engineering Program