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
- Cover
- Title page
- Copyright page
- Dedication
- PREFACE
- CHAPTER 1: WHAT IS SIGNAL PROCESSING?
-
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
- CHAPTER 6: TEMPORAL AND SPATIAL SIGNAL PROCESSING
-
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
Product information
- Title: Digital Signal Processing Using MATLAB for Students and Researchers
- Author(s):
- Release date: August 2011
- Publisher(s): Wiley
- ISBN: 9780470880913
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