Statistical and Adaptive Signal Processing :Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing
Statistical and Adaptive Signal Processing :Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing
hardback
Published:
31 May, 2005
hardback
Published:
31 May, 2005
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Description
Signal processing is an essential topic for all practicing and aspiring electrical engineers to understand no matter what specific area they are involved in. Originally published by McGraw-Hill* and now reissued by Artech House, this definitive volume offers a unified, comprehensive and practical treatment of statistical and adaptive signal processing. Written by leading experts in industry and academia, the book covers the most important aspects of the subject, such as spectral estimation, signal modeling, adaptive filtering, and array processing. This unique resource provides balanced coverage of implementation issues, applications, and theory, making it a smart choice for professional engineers and students alike. The book presents clear examples, problem sets, and computer experiments that help readers master the material and learn how to implement various methods presented in the chapters. This invaluable reference also includes a set of Matlab[registered] functions that engineers can use to solve real-world problems in the field. The book is packed with over 3,000 equations and more than 300 illustrations.
More Details
| Type | Book |
|---|---|
| ISBN13 | 9781580536103 |
| ISBN10 | 1580536107 |
| Number Of Pages | 816 |
| Item Weight | 2153 g |
| Product Dimensions | 216 x 280 x 42 mm |
| Publisher / Reseller | Artech House Publishers |
| Format | hardback |
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Author's Bio
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.