DIGITAL SIGNAL PROCESSING USING MATLAB FOR STUDENTS AND RESEARCHERS -- CONTENTS -- PREFACE -- CHAPTER 1: WHAT IS SIGNAL PROCESSING? -- 1.1 CHAPTER OBJECTIVES -- 1.2 INTRODUCTION -- 1.3 BOOK OBJECTIVES -- 1.4 DSP AND ITS APPLICATIONS -- 1.5 APPLICATION CASE STUDIES USING DSP -- 1.6 OVERVIEW OF LEARNING OBJECTIVES -- 1.7 CONVENTIONS USED IN THIS BOOK -- 1.8 CHAPTER SUMMARY -- CHAPTER 2: MATLAB FOR SIGNAL PROCESSING -- 2.1 CHAPTER OBJECTIVES -- 2.2 INTRODUCTION -- 2.3 WHAT IS MATLAB? -- 2.4 GETTING STARTED -- 2.5 EVERYTHING IS A MATRIX -- 2.6 INTERACTIVE USE -- 2.7 TESTING AND LOOPING -- 2.8 FUNCTIONS AND VARIABLES -- 2.9 PLOTTING AND GRAPHING -- 2.10 LOADING AND SAVING DATA -- 2.11 MULTIDIMENSIONAL ARRAYS -- 2.12 BITWISE OPERATORS -- 2.13 VECTORIZING CODE -- 2.14 USING MATLAB FOR PROCESSING SIGNALS -- 2.15 CHAPTER SUMMARY -- CHAPTER 3: SAMPLED SIGNALS AND DIGITAL PROCESSING -- 3.1 CHAPTER OBJECTIVES -- 3.2 INTRODUCTION -- 3.3 PROCESSING SIGNALS USING COMPUTER ALGORITHMS -- 3.4 DIGITAL REPRESENTATION OF NUMBERS -- 3.5 SAMPLING -- 3.6 QUANTIZATION -- 3.7 IMAGE DISPLAY -- 3.8 ALIASING -- 3.9 RECONSTRUCTION -- 3.10 BLOCK DIAGRAMS AND DIFFERENCE EQUATIONS -- 3.11 LINEARITY, SUPERPOSITION, AND TIME INVARIANCE -- 3.12 PRACTICAL ISSUES AND COMPUTATIONAL EFFICIENCY -- 3.13 CHAPTER SUMMARY -- CHAPTER 4: RANDOM SIGNALS -- 4.1 CHAPTER OBJECTIVES -- 4.2 INTRODUCTION -- 4.3 RANDOM AND DETERMINISTIC SIGNALS -- 4.4 RANDOM NUMBER GENERATION -- 4.5 STATISTICAL PARAMETERS -- 4.6 PROBABILITY FUNCTIONS -- 4.7 COMMON DISTRIBUTIONS -- 4.8 CONTINUOUS AND DISCRETE VARIABLES -- 4.9 SIGNAL CHARACTERIZATION -- 4.10 HISTOGRAM OPERATORS -- 4.11 MEDIAN FILTERS -- 4.12 CHAPTER SUMMARY -- CHAPTER 5: REPRESENTING SIGNALS AND SYSTEMS -- 5.1 CHAPTER OBJECTIVES -- 5.2 INTRODUCTION -- 5.3 DISCRETE-TIME WAVEFORM GENERATION -- 5.4 THE z TRANSFORM.

5.5 POLYNOMIAL APPROACHThe previous section showed how to iterate a difference equation in order to determinethe output sequence. It is particularly important to understand the relationshipbetween difference equations and their transforms. The z transform of a linear systemgives us the key to combining systems together to form more complex systems, sincethe z transforms in combined blocks are able to be multiplied or added together asnecessary. We now give another insight into this approach.Supp -- 5.6 POLES, ZEROS, AND STABILITY -- 5.7 TRANSFER FUNCTIONS AND FREQUENCY RESPONSE -- 5.8 VECTOR INTERPRETATION OF FREQUENCY RESPONSE -- 5.9 CONVOLUTION -- 5.10 CHAPTER SUMMARY -- CHAPTER 6: TEMPORAL AND SPATIAL SIGNAL PROCESSING -- 6.1 CHAPTER OBJECTIVES -- 6.2 INTRODUCTION -- 6.3 CORRELATION -- 6.4 LINEAR PREDICTION -- 6.5 NOISE ESTIMATION AND OPTIMAL FILTERING -- 6.6 TOMOGRAPHY -- 6.7 CHAPTER SUMMARY -- CHAPTER 7: FREQUENCY ANALYSIS OF SIGNALS -- 7.1 CHAPTER OBJECTIVES -- 7.2 INTRODUCTION -- 7.3 FOURIER SERIES -- 7.4 HOW DO THE FOURIER SERIES COEFFICIENT EQUATIONS COME ABOUT? -- 7.5 PHASE-SHIFTED WAVEFORMS -- 7.6 THE FOURIER TRANSFORM -- 7.7 ALIASING IN DISCRETE-TIME SAMPLING -- 7.8 THE FFT AS A SAMPLE INTERPOLATOR -- 7.9 SAMPLING A SIGNAL OVER A FINITE TIME WINDOW -- 7.10 TIME-FREQUENCY DISTRIBUTIONS -- 7.11 BUFFERING AND WINDOWING -- 7.12 THE FFT -- 7.13 THE DCT -- 7.14 CHAPTER SUMMARY -- CHAPTER 8: DISCRETE-TIME FILTERS -- 8.1 CHAPTER OBJECTIVES -- 8.2 INTRODUCTION -- 8.3 WHAT DO WE MEAN BY "FILTERING"? -- 8.4 FILTER SPECIFICATION, DESIGN, AND IMPLEMENTATION -- 8.5 FILTER RESPONSES -- 8.6 NONRECURSIVE FILTER DESIGN -- 8.7 IDEAL RECONSTRUCTION FILTER -- 8.8 FILTERS WITH LINEAR PHASE -- 8.9 FAST ALGORITHMS FOR FILTERING, CONVOLUTION, AND CORRELATION -- 8.10 CHAPTER SUMMARY -- CHAPTER 9: RECURSIVE FILTERS -- 9.1 CHAPTER OBJECTIVES -- 9.2 INTRODUCTION.

9.3 ESSENTIAL ANALOG SYSTEM THEORY -- 9.4 CONTINUOUS-TIME RECURSIVE FILTERS -- 9.5 COMPARING CONTINUOUS-TIME FILTERS -- 9.6 CONVERTING CONTINUOUS-TIME FILTERS TO DISCRETE FILTERS -- 9.7 SCALING AND TRANSFORMATION OF CONTINUOUS FILTERS -- 9.8 SUMMARY OF DIGITAL FILTER DESIGN VIA ANALOG APPROXIMATION -- 9.9 CHAPTER SUMMARY -- BIBLIOGRAPHY -- INDEX.