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Digital Signal Processing Using MATLAB for Students and Researchers

Book Description

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

  1. Cover
  2. Title page
  3. Copyright page
  4. Dedication
  5. PREFACE
  6. CHAPTER 1: WHAT IS SIGNAL PROCESSING?
    1. 1.1 CHAPTER OBJECTIVES
    2. 1.2 INTRODUCTION
    3. 1.3 BOOK OBJECTIVES
    4. 1.4 DSP AND ITS APPLICATIONS
    5. 1.5 APPLICATION CASE STUDIES USING DSP
    6. 1.6 OVERVIEW OF LEARNING OBJECTIVES
    7. 1.7 CONVENTIONS USED IN THIS BOOK
    8. 1.8 CHAPTER SUMMARY
  7. CHAPTER 2: MATLAB FOR SIGNAL PROCESSING
    1. 2.1 CHAPTER OBJECTIVES
    2. 2.2 INTRODUCTION
    3. 2.3 WHAT IS MATLAB?
    4. 2.4 GETTING STARTED
    5. 2.5 EVERYTHING IS A MATRIX
    6. 2.6 INTERACTIVE USE
    7. 2.7 TESTING AND LOOPING
    8. 2.8 FUNCTIONS AND VARIABLES
    9. 2.9 PLOTTING AND GRAPHING
    10. 2.10 LOADING AND SAVING DATA
    11. 2.11 MULTIDIMENSIONAL ARRAYS
    12. 2.12 BITWISE OPERATORS
    13. 2.13 VECTORIZING CODE
    14. 2.14 USING MATLAB FOR PROCESSING SIGNALS
    15. 2.15 CHAPTER SUMMARY
  8. CHAPTER 3: SAMPLED SIGNALS AND DIGITAL PROCESSING
    1. 3.1 CHAPTER OBJECTIVES
    2. 3.2 INTRODUCTION
    3. 3.3 PROCESSING SIGNALS USING COMPUTER ALGORITHMS
    4. 3.4 DIGITAL REPRESENTATION OF NUMBERS
    5. 3.5 SAMPLING
    6. 3.6 QUANTIZATION
    7. 3.7 IMAGE DISPLAY
    8. 3.8 ALIASING
    9. 3.9 RECONSTRUCTION
    10. 3.10 BLOCK DIAGRAMS AND DIFFERENCE EQUATIONS
    11. 3.11 LINEARITY, SUPERPOSITION, AND TIME INVARIANCE
    12. 3.12 PRACTICAL ISSUES AND COMPUTATIONAL EFFICIENCY
    13. 3.13 CHAPTER SUMMARY
  9. CHAPTER 4: RANDOM SIGNALS
    1. 4.1 CHAPTER OBJECTIVES
    2. 4.2 INTRODUCTION
    3. 4.3 RANDOM AND DETERMINISTIC SIGNALS
    4. 4.4 RANDOM NUMBER GENERATION
    5. 4.5 STATISTICAL PARAMETERS
    6. 4.6 PROBABILITY FUNCTIONS
    7. 4.7 COMMON DISTRIBUTIONS
    8. 4.8 CONTINUOUS AND DISCRETE VARIABLES
    9. 4.9 SIGNAL CHARACTERIZATION
    10. 4.10 HISTOGRAM OPERATORS
    11. 4.11 MEDIAN FILTERS
    12. 4.12 CHAPTER SUMMARY
  10. CHAPTER 5: REPRESENTING SIGNALS AND SYSTEMS
    1. 5.1 CHAPTER OBJECTIVES
    2. 5.2 INTRODUCTION
    3. 5.3 DISCRETE-TIME WAVEFORM GENERATION
    4. 5.4 THE z TRANSFORM
    5. 5.5 POLYNOMIAL APPROACH
    6. 5.6 POLES, ZEROS, AND STABILITY
    7. 5.7 TRANSFER FUNCTIONS AND FREQUENCY RESPONSE
    8. 5.8 VECTOR INTERPRETATION OF FREQUENCY RESPONSE
    9. 5.9 CONVOLUTION
    10. 5.10 CHAPTER SUMMARY
  11. CHAPTER 6: TEMPORAL AND SPATIAL SIGNAL PROCESSING
    1. 6.1 CHAPTER OBJECTIVES
    2. 6.2 INTRODUCTION
    3. 6.3 CORRELATION
    4. 6.4 LINEAR PREDICTION
    5. 6.5 NOISE ESTIMATION AND OPTIMAL FILTERING
    6. 6.6 TOMOGRAPHY
    7. 6.7 CHAPTER SUMMARY
  12. CHAPTER 7: FREQUENCY ANALYSIS OF SIGNALS
    1. 7.1 CHAPTER OBJECTIVES
    2. 7.2 INTRODUCTION
    3. 7.3 FOURIER SERIES
    4. 7.4 HOW DO THE FOURIER SERIES COEFFICIENT EQUATIONS COME ABOUT?
    5. 7.5 PHASE-SHIFTED WAVEFORMS
    6. 7.6 THE FOURIER TRANSFORM
    7. 7.7 ALIASING IN DISCRETE-TIME SAMPLING
    8. 7.8 THE FFT AS A SAMPLE INTERPOLATOR
    9. 7.9 SAMPLING A SIGNAL OVER A FINITE TIME WINDOW
    10. 7.10 TIME-FREQUENCY DISTRIBUTIONS
    11. 7.11 BUFFERING AND WINDOWING
    12. 7.12 THE FFT
    13. 7.13 THE DCT
    14. 7.14 CHAPTER SUMMARY
  13. CHAPTER 8: DISCRETE-TIME FILTERS
    1. 8.1 CHAPTER OBJECTIVES
    2. 8.2 INTRODUCTION
    3. 8.3 WHAT DO WE MEAN BY “FILTERING”?
    4. 8.4 FILTER SPECIFICATION, DESIGN, AND IMPLEMENTATION
    5. 8.5 FILTER RESPONSES
    6. 8.6 NONRECURSIVE FILTER DESIGN
    7. 8.7 IDEAL RECONSTRUCTION FILTER
    8. 8.8 FILTERS WITH LINEAR PHASE
    9. 8.9 FAST ALGORITHMS FOR FILTERING, CONVOLUTION, AND CORRELATION
    10. 8.10 CHAPTER SUMMARY
  14. CHAPTER 9: RECURSIVE FILTERS
    1. 9.1 CHAPTER OBJECTIVES
    2. 9.2 INTRODUCTION
    3. 9.3 ESSENTIAL ANALOG SYSTEM THEORY
    4. 9.4 CONTINUOUS-TIME RECURSIVE FILTERS
    5. 9.5 COMPARING CONTINUOUS-TIME FILTERS
    6. 9.6 CONVERTING CONTINUOUS-TIME FILTERS TO DISCRETE FILTERS
    7. 9.7 SCALING AND TRANSFORMATION OF CONTINUOUS FILTERS
    8. 9.8 SUMMARY OF DIGITAL FILTER DESIGN VIA ANALOG APPROXIMATION
    9. 9.9 CHAPTER SUMMARY
  15. BIBLIOGRAPHY
  16. INDEX