Digital and Statistical Signal Processing

Description

Nowadays, many aspects of electrical and electronic engineering are essentially applications of DSP. This is due to the focus on processing information in the form of digital signals, using certain DSP hardware designed to execute software. Fundamental topics in digital signal processing are introduced with theory, analytical tables, and applications with simulation tools. The book provides a collection of solved problems on digital signal processing and statistical signal processing. The solutions are based directly on the math-formulas given in extensive tables throughout the book, so the reader can solve practical problems on signal processing quickly and efficiently. FEATURES Explains how applications of DSP can be implemented in certain programming environments designed for real time systems, ex. biomedical signal analysis and medical image processing. Pairs theory with basic concepts and supporting analytical tables. Includes an extensive collection of solved problems throughout the text. Fosters the ability to solve practical problems on signal processing without focusing on extended theory. Covers the modeling process and addresses broader fundamental issues. Content: Cover Half Title Title Page Copyright Page Dedication Table of Contents Preface Authors List of Acronyms Section I : Topics on Digital Signal Processing Chapter 1: Introduction 1.1 Introduction 1.2 Advantages of Digital Signal Processing 1.3 Digitization Steps of Analog Signals 1.3.1 Sampling 1.3.2 Quantization 1.3.3 Coding 1.4 Sampling and Reconstruction of Sinusoidal Signals 1.4.1 Proof of the Sampling Theorem and a Detailed Discussion 1.5 Physical Sampling 1.6 Sampling and Holding 1.7 Non-Accurate Reconstruction of Analog Signals 1.8 SOLVED PROBLEMS. Chapter 2: Discrete-Time Signals and Systems2.1 Discrete-Time Signals 2.2 Basic Discrete-Time Signals 2.2.1 Impulse Function 2.2.2 Unit Step Function 2.2.3 Ramp Function 2.2.4 Unit Rectangular Function (Pulse Function) 2.2.5 Exponential Function 2.2.6 The Sinusoidal Sequence 2.3 Even and Odd Discrete-Time Signals 2.4 Energy and Power of a Discrete-Time Signal 2.5 Conversion of the Independent and Dependant Variable 2.6 Discrete-Time Systems 2.7 Categories of Discrete-Time Systems 2.7.1 Linear Discrete Systems 2.7.2 Time-Invariant Discrete Systems. 2.7.3 Discrete Systems with Memory2.7.4 Invertible Discrete Systems 2.7.5 Casual Discrete Systems 2.7.6 Stable Discrete Systems 2.8 System Connections 2.9 Convolution 2.10 Deconvolution 2.11 Correlation -- Autocorrelation 2.12 Difference Equations 2.13 Discrete-Time Systems of Finite Impulse Response 2.14 Solved Problems Chapter 3: z-Transform 3.1 Introduction 3.2 From Laplace Transform to z-Transform 3.2.1 Comparison of the s- and z-Planes into the Region of Convergence 3.3 Properties of z-Transform 3.3.1 Time Shift 3.3.2 Linearity 3.3.3 Time Reversal 3.3.4 Convolution. 3.3.5 Differentiation in z-Plane3.3.6 Multiplication by an Exponential Sequence 3.3.7 Conjugation of a Complex Sequence 3.3.8 Initial and Final Value Theorem 3.3.9 Correlation of Two Sequences 3.4 Inverse z-Transform 3.4.1 Method of Power Series Expansion (Division Method) 3.4.2 Method of Partial Fraction Expansion 3.4.3 Method of Complex Integration 3.5 z-Transform in System Analysis 3.5.1 Transfer Function of Discrete-Time Signal 3.5.2 Causality of Discrete-Time Systems 3.5.3 Stability of Discrete-Time Systems 3.5.4 Transfer Function of Connected Systems. 3.5.5 Transfer Function of Discrete-Time Systems3.6 Formula Tables 3.7 Solved Problems Chapter 4: Structures for the Realization of Discrete-Time Systems 4.1 Introduction 4.2 Block Diagrams 4.3 Realization Structures 4.3.1 Implementation Structures of IIR Discrete Systems 4.3.2 Implementation Structures of FIR Discrete Systems 4.4 Signal Flow Graphs 4.4.1 Mason's Gain Formula 4.5 Solved Problems Chapter 5: Frequency Domain Analysis 5.1 Introduction 5.2 Discrete-Time Fourier Transform (DTFT) 5.3 Discrete Fourier Series (DFS) 5.3.1 Periodic Convolution.