Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing

This authoritative volume on statistical and adaptive signal processing offers you a unified, comprehensive and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. Packed with over 3,000 equations and more than 300 illustrations, this unique resource provides you with balanced coverage of implementation issues, applications, and theory, making it a smart choice for professional engineers and students alike.

The text is written in an intuitive manner and includes many illustrative examples. In addition a sufficient number of computer based experiments are included that illustrate important concepts to the reader for ease of implementation. Throughout the book a sufficient emphasis has been placed on applications for the purposes of demonstrating the utility of various techniques.

Dimitris G. Manolakis is a member of the technical staff at M.I.T. Lincoln Laboratory. Previously, he was a principal member of the research staff at Riverside Research Institute.

Vinay K. Ingle is an associate professor of electrical and computer engineering at Northeastern University.

Stephen M. Kogon is a member of the technical staff at M.I.T. Lincoln Laboratory. Previously, he has been associated with Raytheon Co., Boston College, and Georgia Tech Research Institute.