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Full Description
Optimum and Adaptive Signal Processing has been developed in a simple, logical and directed way. The ease of understanding is facilitated by providing all the intermediate steps in a mathematical expression derivation and its physical meaning, preserving the rigour and depth of the subject. Chapters 2 to 5, covering the background, make the book self-contained. The detailed treatment of both optimum and adaptive processing (unlike in some of the other books), enables enhanced understanding. Also, chapters 1-8 and 9-17, can function as independent books on optimum signal processing and adaptive signal processing (for those with optimum signal processing background), respectively.
Contents
1. Introduction
2. Signal Approximation: The Fourier Transform
3. Signal Transmission and Power Spectral Density
4. Sampling Theorem and Discrete Fourier Transform
5. Random Signal Theory
6. Non-parametric Spectral Estimation
7. Parametric Spectral Estimation
8. Parametric Approach in Its General form - The Wiener Filter
9. Iterative Solution to Normal Equations: Method of Steepest Descent
10. Least Mean Square (LMS) Algorithm
11. Orthogonalization Based Least Mean Square Algorithm
12. Subband and Wavelet Adaptive Filters
13. Adaptive Infinite Impulse Response (IIR) Filters
14. Block /Frequency Domain LMS Algorithm
15. Recursive Least Square Adaptive Filters
16. Nonlinear Adaptive Filters
17 Applications of Adaptive Filters



