Digital Signal Processing Using MATLAB for Students and Researchers 1st Edition by John Leis ISBN 978-0470880913 0470880910

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Product details: 

ISBN 10: 0470880910

ISBN 13: 978-0470880913

Author:  John W. Leis

Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing Problems

With its active, hands-on learning approach, this text enables readers to master the underlying principles of digital signal processing and its many applications in industries such as digital television, mobile and broadband communications, and medical/scientific devices. Carefully developed MATLAB® examples throughout the text illustrate the mathematical concepts and use of digital signal processing algorithms. Readers will develop a deeper understanding of how to apply the algorithms by manipulating the codes in the examples to see their effect. Moreover, plenty of exercises help to put knowledge into practice solving real-world signal processing challenges.

Following an introductory chapter, the text explores:

Sampled signals and digital processing

Random signals

Representing signals and systems

Temporal and spatial signal processing

Frequency analysis of signals

Discrete-time filters and recursive filters

Each chapter begins with chapter objectives and an introduction. A summary at the end of each chapter ensures that one has mastered all the key concepts and techniques before progressing in the text. Lastly, appendices listing selected web resources, research papers, and related textbooks enable the investigation of individual topics in greater depth.

Upon completion of this text, readers will understand how to apply key algorithmic techniques to address practical signal processing problems as well as develop their own signal processing algorithms. Moreover, the text provides a solid foundation for evaluating and applying new digital processing signal techniques as they are developed.

Table of contents: 

Chapter 1: What Is Signal Processing?

• Chapter Objectives

• Introduction

• Book Objectives

• DSP and Its Applications

• Application Case Studies Using DSP

• Overview of Learning Objectives

• Conventions Used in This Book

• Chapter Summary

Chapter 2: Matlab for Signal Processing

• Chapter Objectives

• Introduction

• What Is MATLAB?

• Getting Started

• Everything Is a Matrix

• Interactive Use

• Testing and Looping

• Functions and Variables

• Plotting and Graphing

• Loading and Saving Data

• Multidimensional Arrays

• Bitwise Operators

• Vectorizing Code

• Using MATLAB for Processing Signals

• Chapter Summary

Chapter 3: Sampled Signals and Digital Processing

• Chapter Objectives

• Introduction

• Processing Signals Using Computer Algorithms

• Digital Representation of Numbers

• Sampling

• Quantization

• Image Display

• Aliasing

• Reconstruction

• Block Diagrams and Difference Equations

• Linearity, Superposition, and Time Invariance

• Practical Issues and Computational Efficiency

• Chapter Summary

Chapter 4: Random Signals

• Chapter Objectives

• Introduction

• Random and Deterministic Signals

• Random Number Generation

• Statistical Parameters

• Probability Functions

• Common Distributions

• Continuous and Discrete Variables

• Signal Characterization

• Histogram Operators

• Median Filters

• Chapter Summary

Chapter 5: Representing Signals and Systems

• Chapter Objectives

• Introduction

• Discrete-Time Waveform Generation

• The z Transform

• Polynomial Approach

• Poles, Zeros, and Stability

• Transfer Functions and Frequency Response

• Vector Interpretation of Frequency Response

• Convolution

• Chapter Summary

Chapter 6: Temporal and Spatial Signal Processing

• Chapter Objectives

• Introduction

• Correlation

• Linear Prediction

• Noise Estimation and Optimal Filtering

• Tomography

• Chapter Summary

Chapter 7: Frequency Analysis of Signals

• Chapter Objectives

• Introduction

• Fourier Series

• How Do the Fourier Series Coefficient Equations Come About?

• Phase-Shifted Waveforms

• The Fourier Transform

• Aliasing in Discrete-Time Sampling

• The FFT as a Sample Interpolator

• Sampling a Signal over a Finite Time Window

• Time-Frequency Distributions

• Buffering and Windowing

• The FFT

• The DCT

• Chapter Summary

Chapter 8: Discrete-Time Filters

• Chapter Objectives

• Introduction

• What Do We Mean by “Filtering”?

• Filter Specification, Design, and Implementation

• Filter Responses

• Nonrecursive Filter Design

• Ideal Reconstruction Filter

• Filters with Linear Phase

• Fast Algorithms for Filtering, Convolution, and Correlation

• Chapter Summary

Chapter 9: Recursive Filters

• Chapter Objectives

• Introduction

• Essential Analog System Theory

• Continuous-Time Recursive Filters

• Comparing Continuous-Time Filters

• Converting Continuous-Time Filters to Discrete Filters

• Scaling and Transformation of Continuous Filters

• Summary of Digital Filter Design via Analog Approximation

• Chapter Summary

Bibliography
Index

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Tags: John Leis, Digital Signal Processing, Using MATLAB, Students and Researchers