Adaptive Filter Theory

Adaptive Filter Theory

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This book develops the mathematical theory of linear adaptive filters with finite impulse response. Examples and computer experiment applications illustrate the theory and principles. The second edition has also been restructured with an introduction followed by four parts: discrete-time wide-sense station stochastic process; linear optimum filtering; linear FIR adaptive filtering; limitations, extensions and discussions. New features includes new chapters on QR decomposition-based lattice filters, on blind deconvolution, new appendix material on complex variables and regulation.
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Product details

  • Hardback | 704 pages
  • 177.8 x 236.22 x 40.64mm | 1,406.13g
  • Prentice-Hall
  • Harlow, United Kingdom
  • Revised
  • 2nd Revised edition
  • 0130132365
  • 9780130132369

Table of contents

Discrete-time side-sense stationary stochastic processes - stationary processes and models; spectrum analysis; eigenanalysis. Linear optimum filtering - Wiener filters; linear prediction; Kalman filters. Linear Fir adaptive filtering - method of steepest descent; stochastic gradient-based algorithms; linear least-squares estimation; method of least squares; singular value decomposition; super-resolution algorithms using eigenvector-based projects; standard recursive least squares estimation; recursive least-squares systolic arrays; background theory for fast recursive algorithms; fast transversal filters; recursive least-squares lattice filters; QR decomposition-based least squares lattice filters. Limitations, extensions and discussions - finite-precision and other practical effects; blind convolution; discussion.
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Rating details

48 ratings
4.1 out of 5 stars
5 48% (23)
4 27% (13)
3 17% (8)
2 4% (2)
1 4% (2)
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