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Adaptive Filter Theory

Adaptive Filter Theory

  • Simon Haykin
  • Author: Simon Haykin
    • ISBN:9788131708699
    • 10 Digit ISBN:8131708691
    • Price:Rs. 979.00
    • Pages:936
    • Imprint:Pearson Education
    • Binding:Paperback
    • Status:Available


    For courses in Adaptive Filters.

    Haykin examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons. In its fourth edition, this highly successful book has been updated and refined to stay current with the field and develop concepts in as unified and accessible a manner as possible.

    Table of Content

    1. Stochastic Processes and Models.
    2. Wiener Filters.
    3. Linear Prediction.
    4. Method of Steepest Descent.
    5. Least-Mean-Square Adaptive Filters.
    6. Normalized Least-Mean-Square Adaptive Filters.
    7. Transform-Domain and Sub-Band Adaptive Filters.
    8. Method of Least Squares.
    9. Recursive Least-Square Adaptive Filters.
    10. Kalman Filters as the Unifying Bases for RLS Filters.
    11. Square-Root Adaptive Filters.
    12. Order-Recursive Adaptive Filters.
    13. Finite-Precision Effects.
    14. Tracking of Time-Varying Systems.
    15. Adaptive Filters Using Infinite-Duration Impulse Response Structures.
    16. Blind Deconvolution.
    17. Back-Propagation Learning.

    Salient Features

    • Improves the presentation of material on statistical LMS theory and statistical RLS theory.
    • Expands the treatment of normalized LMS filters, and introduces the more general case of affine projection filters.
    • Introduces sub-band adaptive filters.
    • Repositions the teaching of Kalman filters after the treatment of RLS filters, thereby enhancing the unified treatment of square-root adaptive filters and order recursive adaptive filters.
    • In-depth treatment of adaptive filters in a highly readable and understandable fashion.
    • Major revision of the MATLAB codes for the computer experiments—Available on the web.
    • Extensive use of MATLAB experiments—Illustrates the practical realities and intricacies of adaptive filters, the codes for which can be downloaded from the Web.