Optimum and Adaptive Signal Processing

Contents: 1. Introduction. 2. Signal Approximation: The Fourier Transform. 3. Signal Transmission and Power Spectral Density. 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. 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 cater as books on optimum signal processing and adaptive signal processing (for those with optimum signal processing background), respectively. (jacket).…