Acknowledgements; Contents; 1 Sampling and Reconstruction of Signals ; 1.1 Sampling of Sinusoidal Signal; 1.2 Fourier Series (FS); 1.2.1 Dirichlet Conditions; 1.3 Fourier Transformation (FT); 1.4 Discrete Time Fourier Transformation (DTFT) and Sampling Theorem; 1.5 Discrete Fourier Transformation (DFT) (Sampling the Frequency Domain); 1.5.1 Vector Space Interpretation of DFT; 1.5.2 Fast Fourier Transformation; 1.5.3 Sub-band Discrete Fourier Transformation; 1.6 Continous System; 1.7 Laplace Transformation (s-Transformation) 1.7.1 Properties of the ROC of the Laplace Transformation for the Right Sided Sequence1.7.2 Inverse Laplace Transformation; 1.8 Geometrical Interpretation of Computation of Magnitude Response of the Filter Using Pole-Zero Plot of s-Transformation; 1.9 Discrete System; 1.10 Z-Transformation; 1.10.1 Properties of the ROC of the Z-Transformation for the Right-Sided Sequence; 1.10.2 Inverse Z-Transformation; 1.11 Response of the Digital Filter with the Typical Transfer Function#x83;; 1.12 Geometrical Interpretation of Computation of Magnitude #x83;; 2 Infinite Impulse Response (IIR) Filter 2.1 Impulse-Invariant Mapping2.2 Bilinear Transformation Mapping; 2.2.1 Frequency Pre-warping; 2.2.2 Design of Digital IIR Filter using Butterworth Analog Filter and Impulse-Invariant Transformation; 2.2.3 Design of Digital IIR Filter using Butterworth Analog Filter and Bilinear Transformation; 2.2.4 Design of Digital IIR Filter Using Chebyshev Analog Filter and Impulse-Invariant Transformation; 2.2.5 Design of Digital IIR Filter Using Chebyshev Analog Filter and Bilinear Transformation; 2.2.6 Comments on Fig. 2.7 and Fig. 2.8; 2.2.7 Design of High-Pass, Bandpass, and Band-Reject IIR Filter 2.3 Realization2.3.1 Direct Form 1; 2.3.2 Direct Form 2; 2.3.3 Illustration; 3 Finite Impulse Response Filter (FIR Filter); 3.1 Demonstration of Four Types of FIR Filter; 3.2 Design of Linear Phase FIR Filter-Windowing Technique; 3.2.1 Design of Low-Pass Filter; 3.2.2 Design of High-Pass Filter; 3.2.3 Design of Band Pass and Band Reject Filter; 3.2.4 Windows Used to Circumvent Ripples in the Magnitude Response; 3.3 FIR Filters that Have Identical Magnitude Response; 4 Multirate Digital Signal Processing; 4.1 Sampling Rate Conversion by the Factor MN; 4.1.1 Upsampling (with N=1) 4.1.2 Downsampling (with M=1)4.1.3 Comments on the Fig.4.1; 4.2 Poly-phase Realization of the Filter for Interpolation; 4.3 Poly-phase Realization of the Filter for Decimation; 4.4 Quadrature Mirror Filter; 4.5 Transmultiplexer; 5 Statistical Signal Processing; 5.1 Introduction to Random Process; 5.1.1 Illustration on W.S.S.R.P and Nonstationary Random Process; 5.2 Auto Regressive (AR), Moving average (MA) #x83;; 5.2.1 Linear Prediction Model; 5.3 Adaptive Filter; 5.3.1 System Model; 5.3.2 Filtering Noise; 5.4 Spectral Estimation; 5.4.1 Eigen Decomposition Method for Spectral Estimation.

This book provides a comprehensive overview of digital signal processing for a multi-disciplinary audience. It posits that though the theory involved in digital signal processing stems from electrical, electronics, communication, and control engineering, the topic has use in other disciplinary areas like chemical, mechanical, civil, computer science, and management. This book is written about digital signal processing in such a way that it is suitable for a wide ranging audience. Readers should be able to get a grasp of the field, understand the concepts easily, and apply as needed in their own fields. It covers sampling and reconstruction of signals; infinite impulse response filter; finite impulse response filter; multi rate signal processing; statistical signal processing; and applications in multidisciplinary domains. The book takes a functional approach and all techniques are illustrated using Matlab.