Digital signal processing 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 t...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
Wiley
[2011]
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| Edición: | 1st ed |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628295106719 |
Tabla de Contenidos:
- 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 GRAPHING2.10 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 EFFICIENCY3.13 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.S...5.6 POLES, ZEROS, AND STABILITY; 5.7 TRANSFER FUNCTIONS AND FREQUENCY RESPONSE
- 5.8 VECTOR INTERPRETATION OF FREQUENCY RESPONSE5.9 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
