Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing - Hardcover
Synopsis
This book is intended for graduate students at the first year or advanced graduate level in the areas of statistical and adaptive signal processing, as well as practicing engineers. The goal of this book is to provide a unified, complete, and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. 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.
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About the Author
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.
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Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing (McGraw-Hill Series in . Computer Engineering. Computer Engineering)
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Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing
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