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...
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| Main Author | |
|---|---|
| Format | eBook Book |
| Language | English |
| Published |
Hoboken, N.J
Wiley
2011
John Wiley & Sons John Wiley & Sons, Incorporated Wiley-Blackwell |
| Edition | 1st ed. |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9780470880913 9781118033609 1118033604 0470880910 1118033620 9781118033623 |
| DOI | 10.1002/9781118033623 |
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| Abstract | "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" |
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| AbstractList | Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing ProblemsWith 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 processingRandom signalsRepresenting signals and systemsTemporal and spatial signal processingFrequency analysis of signalsDiscrete-time filters and recursive filtersEach 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. "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" 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. |
| Author | Leis, John W |
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| Notes | Includes bibliographical references and index |
| OCLC | 729726215 |
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| PublicationDecade | 2010 |
| PublicationPlace | Hoboken, N.J |
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| Publisher | Wiley John Wiley & Sons John Wiley & Sons, Incorporated Wiley-Blackwell |
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| Snippet | "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,... Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing ProblemsWith its active, hands-on learning approach, this text enables... Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing Problems With its active, hands-on learning approach, this text enables... |
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| SubjectTerms | Data processing Digital techniques Mathematics MATLAB Numerical analysis SCIENCE SCIENCE / Waves & Wave Mechanics bisacsh Signal processing Signal processing -- Digital techniques Signal processing -- Mathematics -- Data processing Waves & Wave Mechanics |
| SubjectTermsDisplay | SCIENCE Waves & Wave Mechanics |
| TableOfContents | 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 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 Intro -- 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 |
| Title | Digital signal processing using MATLAB for students and researchers |
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