Statistical & Adaptive Signal Processing / Edition 1

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Overview

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.

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Product Details

  • ISBN-13: 9781580536103
  • Publisher: Artech House, Incorporated
  • Publication date: 4/30/2011
  • Series: Artech House Signal Processing Library
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 816
  • Sales rank: 266,303
  • Product dimensions: 1.69 (w) x 8.50 (h) x 11.00 (d)

Meet 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. Dr. Manolakis has taught at the University of Athens, Northeastern University, Boston College, and Worchester Polytechnic Institute. He received his Ph.D. in electrical engineering from the University of Athens, Greece. Vinay K. Ingle is an associate professor of electrical and computer engineering at Northeastern University. He has broad research experience and has taught courses on signal and image processing, stochastic processes, and estimation theory. Dr. Ingle received his Ph.D. in electrical engineering from Rensselaer Polytechnic Institute. 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. Dr. Kogon received his Ph.D. in electrical engineering from the Georgia Institute of Technology.

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Table of Contents

Preface
1 Introduction 1
2 Fundamentals of Discrete-Time Signal Processing 33
3 Random Variables, Vectors, and Sequences 75
4 Linear Signal Models 149
5 Nonparametric Power Spectrum Estimation 195
6 Optimum Linear Filters 261
7 Algorithms and Structures for Optimum Linear Filters 333
8 Least-Squares Filtering and Prediction 395
9 Signal Modeling and Parametric Spectral Estimation 445
10 Adaptive Filters 499
11 Array Processing 621
12 Further Topics 691
App. A Matrix Inversion Lemma 745
App. B Gradients and Optimization in Complex Space 747
App. C Matlab Functions 753
App. D Useful Results from Matrix Algebra 755
App. E Minimum Phase Test for Polynomials 767
Bibliography 769
Index 787
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