Digital Signal Processsing Using Matlab For Students And Researchers

This book uses an active learning approach to the topic of digital signal processing (DSP). DSP is a fundamental technology with wide ranging applications as, for example, digital downloads of movies, mobile and broadband communications, digital television, and many other areas. In this book the subject is taught using a “hands-on” experimental approach with MATLAB examples throughout the text to illustrate the mathematical concepts and DSP algorithms developed and explained. Existing books in this area tends to fall into one of two camps – either a highly mathematical treatment with few practical examples of the everyday uses of DSP, or else very verbose and descriptive treatments with little or no mathematical content to back up the topics. The former type of text is excellent as a standard reference, but poor as a learning vehicle. The latter type of text is good for general knowledge, but fails to meet the needs of University students and practicing industry professionals. Students need a learn-by-doing approach, and industry professionals need to come up to speed as rapidly as possible. The book uses MATLAB throughout, inn an established industry and University programming environment. Furthermore, it requires that the reader only have access to the Student/Educational version of MATLAB, not the full commercial version, which is out of reach of most students.

John Leis, PhD, is Associate Professor of Electrical and Computer Engineering at the University of Southern Queensland. He has authored many technical papers in areas involving signal processing and networking. Dr. Leis's interests include signal processing for data compression and coding, medical signal processing, and advanced instrumentation using signal processing algorithms. He has collaborated internationally on various research projects. Dr. Leis has taught the subject material extensively in Australia and also Singapore. He is a Senior Member of the Institution of Electrical & Electronic Engineers and a Member of the Association for Computing Machinery.

1. What is Signal Processing?

1.1 Chapter Objectives.

1.2 Introduction.

1.3 Book Objectives.

1.4 Digital Signal Processing and its Applications.

1.5 Application Case Studies using Digital Signal Processing.

1.6 Overview of Learning Objectives.

1.7 Conventions Used in this Book.

1.8 Chapter Summary.

2. Sampled Signals and Digital Processing.

2.1 Chapter Objectives.

2.2 Introduction.

2.3 Processing Signals using Computer Algorithms.

2.4 Digital Representation of Numbers.

2.5 Sampling.

2.6 Quantization.

2.7 Image Display.

2.8 Aliasing.

2.9 Reconstruction.

2.10 Block Diagrams & Difference Equations.

2.11 Linearity, Superposition and Time-Invariance.

2.12 Practical Issues & Computational Efficiency.

2.13 Chapter Summary.

3. Random Signals.

3.1 Chapter Objectives.

3.2 Introduction.

3.3 Random and Deterministic Signals.

3.4 Random Number Generation.

3.5 Statistical Parameters.

3.6 Probability Functions.

3.7 Common Distributions.

3.8 Continuous and Discrete Variables.

3.9 Signal Characterization.

3.10 Histogram Equalization.

3.11 Median Filters.

3.12 Chapter Summary.

4. Representing Signals & Systems.

4.1 Chapter Objectives.

4.2 Introduction.

4.3 Discrete-Time Waveform Generation.

4.4 The z Transform.

4.5 Polynomial Approach.

4.6 Poles, Zeros and Stability.

4.7 Transfer Functions and Frequency Response.

4.8 Vector Interpretation of Frequency Response.

4.9 Convolution.

4.10 Chapter Summary.

5. Temporal and Spatial Signal Processing.

5.1 Chapter Objectives.

5.2 Introduction.

5.3 Correlation.

5.4 Linear Prediction.

5.5 Noise Estimation and Optimal Filtering.

5.6 Tomography.

5.7 Chapter Summary.

6. Frequency Analysis of Signals.

6.1 Chapter Objectives.

6.2 Introduction.

6.3 Fourier Series.

6.4 How Do the Fourier Series Coefficient Come About?

6.5 Phase Shifted Waveforms.

6.6 The Fourier Transform.

6.7 Aliasing in Discrete-Time Sampling.

6.8 The FFT as a Sample Interpolator.

6.9 Sampling a Signal over a Finite Time Window.

6.10 Time-Frequency Distributions.

6.11 Buffering and Windowing.

6.12 Manual Fourier Transform Calculations.

6.13 The Discrete Cosine Transform (DCT).

6.14 Chapter Summary.

7. Discrete-Time Filters.

7.1 Chapter Objectives.

7.2 Introduction.

7.3 What Do We Mean by “Filtering”?

7.4 Filter Specification, Design & Implementation.

7.5 Filter Responses.

7.6 Nonrecursive Filter Design.

7.7 Ideal Reconstruction Filter.

7.8 Filters with Linear Phase.

7.9 Fast Algorithms for Filtering, Convolution and Correlation.

7.10 Chapter Summary.

8. Recursive Filters.

8.1 Chapter Objectives.

8.2 Introduction.

8.3 Essential Analog System Theory.

8.4 Continuous-time Recursive Filters.

8.5 Comparing Continuous-time Filters.

8.6 Converting Continuous-Time Filters to Discrete Filters.

8.7 Scaling and Transformation of Continuous Filters.

8.8 Summary of Digital Filter Design via Analog Approximation.

8.9 Chapter Summary.

Selected Web References.

Selected Academic Papers.

Selected Textbooks.

Index.