Adaptive filter theory

Author(s)

• Haykin, Simon S.

Bibliographic Information

Adaptive filter theory

Simon Haykin

（Prentice-Hall information and system sciences series）

Prentice-Hall, c1991

2nd ed

• : pbk

Note

Bibliography: p. 817-844

Includes index

Description and Table of Contents

Volume

: pbk ISBN 9780130055132

Description

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.

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
• supter-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.

Volume

ISBN 9780130132369

Description

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.

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.

by "Nielsen BookData"

Details

• NCID: BA12545953
• ISBN:
  • 0130132365
  • 0130055131
• LCCN: 90020418
• Country Code: us
• Title Language Code: eng
• Text Language Code: eng
• Place of Publication: Englewood Cliffs, N.J.
• Pages/Volumes: xx, 854 p.
• Size: 25 cm
• Classification:
  • LCC : TK7872.F5
  • DC19 : 621.3815/324
  • NDC8 : 549.3
• Subject Headings:
  • LCSH : Adaptive filters
• Parent Bibliography ID:
  • BA00285185