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Adaptive filter theory / Simon Haykin, Communications Research Laboratory, McMaster University, Hamilton, Ontario, Canada

By: Material type: TextTextPublication details: Upper Saddle River, New Jersey : Pearson, [2014]Edition: 5th edDescription: xvii, 889 pages : illustrations ; 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780132671453
  • 013267145X
Subject(s): DDC classification:
  • 621.3815824
LOC classification:
  • TK7872.F5 H368 2014
  • TK7872.F5 H368 2014
Contents:
Preface -- Acknowledgments -- Background and preview -- Stochastic processes and models -- Wiener filters -- Linear prediction -- Method of steepest descent -- Method of stochastic gradient descent -- The least-mean-square (LMS) algorithm -- Normalized least-mean-square (LMS) algorithm and its generalization -- Block-adaptive filters -- Method of least-squares -- The recursive least-square (RLS) algorithm -- Robustness -- Finite-precision effects -- Adaptation in nonstationary environments -- Kalman filters -- Square-root adaptive filtering algorithms -- Order-recursive adaptive filtering algorithm -- Blind deconvention -- Epilogue -- Appendix A: Theory of complex variables -- Appendix B: Wirtinger calculus for computing complex gradients -- Appendix C: Method of Lagrange multipliers -- Appendix D: Estimation theory -- Appendix E: Eigenanalysis -- Appendix F: Langevin equation of nonequilibrium thermodynamics -- Appendix G: Rotations and reflections -- Appendix H: Complex Wishart distribution
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Item type Current library Call number Status Date due Barcode
Books Books Centeral Library Second Floor - Engineering & Architecture 621.3815824 H.S.A 2014 (Browse shelf(Opens below)) Available 21822
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621.381548 BDE 2013 Electronic instrumentation and measurements / 621.381548 BDE 2013 Electronic instrumentation and measurements / 621.381548 K.H.E 1971 Electronic instrumentation 621.3815824 H.S.A 2014 Adaptive filter theory / 621.3817 M.J.M 1987 Microelectronics / 621.38195835 L.D.D 1985 Design of logic systems / 621.382 Basics of VLSI Design With VHDL

Preface -- Acknowledgments -- Background and preview -- Stochastic processes and models -- Wiener filters -- Linear prediction -- Method of steepest descent -- Method of stochastic gradient descent -- The least-mean-square (LMS) algorithm -- Normalized least-mean-square (LMS) algorithm and its generalization -- Block-adaptive filters -- Method of least-squares -- The recursive least-square (RLS) algorithm -- Robustness -- Finite-precision effects -- Adaptation in nonstationary environments -- Kalman filters -- Square-root adaptive filtering algorithms -- Order-recursive adaptive filtering algorithm -- Blind deconvention -- Epilogue -- Appendix A: Theory of complex variables -- Appendix B: Wirtinger calculus for computing complex gradients -- Appendix C: Method of Lagrange multipliers -- Appendix D: Estimation theory -- Appendix E: Eigenanalysis -- Appendix F: Langevin equation of nonequilibrium thermodynamics -- Appendix G: Rotations and reflections -- Appendix H: Complex Wishart distribution

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