Digital Signal Processing - Fundamentals and Applications
This textbook presents digital signal processing (DSP) principles, applications, and hardware implementation issues, emphasizing achievable results and conclusions through the presentation of numerous worked examples, while reducing the use of mathematics for an easier grasp of the concepts. Feature...
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| Main Authors | , |
|---|---|
| Format | eBook Book |
| Language | English |
| Published |
Oxford
Elsevier
2008
Academic Press Elsevier Science & Technology |
| Edition | 2 |
| Subjects | |
| Online Access | Get full text |
| ISBN | 0123740908 9780123740908 0124158935 9780124158931 |
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| Abstract | This textbook presents digital signal processing (DSP) principles, applications, and hardware implementation issues, emphasizing achievable results and conclusions through the presentation of numerous worked examples, while reducing the use of mathematics for an easier grasp of the concepts. Features include real-time implementation of DSP algorithms using DSP processors; MATLAB programs for simulations and C programs for real-time DSP; coverage of adaptive filtering with applications to noise reduction and echo cancellation; and applications of DSP to multimedia applications (such as u-law and adaptive differential pulse code modulation, sampling rate conversions, transform coding, and image and video processing) show the relevance of DSP to a key area in industry. This text gives students in electronics, computer engineering and bioengineering an understanding of essential DSP principles and implementation, demonstrating how the subject is fundamental to engineering as practiced today. |
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| AbstractList | Digital Signal Processing, Second Edition enables electrical engineers and technicians in the fields of biomedical, computer, and electronics engineering to master the essential fundamentals of DSP principles and practice. Many instructive worked examples are used to illustrate the material, and the use of mathematics is minimized for easier grasp of concepts. As such, this title is also useful to undergraduates in electrical engineering, and as a reference for science students and practicing engineers. The book goes beyond DSP theory, to show implementation of algorithms in hardware and software. Additional topics covered include adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as PCM, u-law, ADPCM, and multi-rate DSP and over-sampling ADC. New to this edition: MATLAB projects dealing with practical applications added throughout the bookNew chapter (chapter 13) covering sub-band coding and wavelet transforms, methods that have become popular in the DSP fieldNew applications included in many chapters, including applications of DFT to seismic signals, electrocardiography data, and vibration signalsAll real-time C programs revised for the TMS320C6713 DSKCovers DSP principles with emphasis on communications and control applicationsChapter objectives, worked examples, and end-of-chapter exercises aid the reader in grasping key concepts and solving related problemsWebsite with MATLAB programs for simulation and C programs for real-time DSP. This book will enable electrical engineers and technicians in the fields of the biomedical, computer, and electronics engineering, to master the essential fundamentals of DSP principles and practice. Coverage includes DSP principles, applications, and hardware issues with an emphasis on applications. Many instructive worked examples are used to illustrate the material and the use of mathematics is minimized for easier grasp of concepts.In addition to introducing commercial DSP hardware and software, and industry standards that apply to DSP concepts and algorithms, topics covered include adaptive filtering with noise reduction and echo cancellations; speech compression; signal sampling, digital filter realizations; filter design; multimedia applications; over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as PCM, u-law, ADPCM, and multi-rate DSP and over-sampling ADC. *Covers DSP principles and hardware issues with emphasis on applications and many worked examples*Website with MATLAB programs for simulation and C programs for real-time DSP*End of chapter problems are helpful in ensuring retention and understanding of what was just read Digital Signal Processing, Second Edition enables electrical engineers and technicians in the fields of biomedical, computer, and electronics engineering to master the essential fundamentals of DSP principles and practice. Many instructive worked examples are used to illustrate the material, and the use of mathematics is minimized for easier grasp of concepts. As such, this title is also useful to undergraduates in electrical engineering, and as a reference for science students and practicing engineers. The book goes beyond DSP theory, to show implementation of algorithms in hardware and software. Additional topics covered include adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as PCM, u-law, ADPCM, and multi-rate DSP and over-sampling ADC. New to this edition: MATLAB projects dealing with practical applications added throughout the bookNew chapter (chapter 13) covering sub-band coding and wavelet transforms, methods that have become popular in the DSP fieldNew applications included in many chapters, including applications of DFT to seismic signals, electrocardiography data, and vibration signalsAll real-time C programs revised for the TMS320C6713 DSK Covers DSP principles with emphasis on communications and control applicationsChapter objectives, worked examples, and end-of-chapter exercises aid the reader in grasping key concepts and solving related problemsWebsite with MATLAB programs for simulation and C programs for real-time DSP Finally! A book that bridges the gap that separates DSP theory and hardware design. This textbook presents digital signal processing (DSP) principles, applications, and hardware implementation issues, emphasizing achievable results and conclusions through the presentation of numerous worked examples, while reducing the use of mathematics for an easier grasp of the concepts. Features include real-time implementation of DSP algorithms using DSP processors; MATLAB programs for simulations and C programs for real-time DSP; coverage of adaptive filtering with applications to noise reduction and echo cancellation; and applications of DSP to multimedia applications (such as u-law and adaptive differential pulse code modulation, sampling rate conversions, transform coding, and image and video processing) show the relevance of DSP to a key area in industry. This text gives students in electronics, computer engineering and bioengineering an understanding of essential DSP principles and implementation, demonstrating how the subject is fundamental to engineering as practiced today. |
| Author | Jiang, Jean Tan, Li |
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| Snippet | This textbook presents digital signal processing (DSP) principles, applications, and hardware implementation issues, emphasizing achievable results and... Digital Signal Processing, Second Edition enables electrical engineers and technicians in the fields of biomedical, computer, and electronics engineering to... Finally! A book that bridges the gap that separates DSP theory and hardware design. This book will enable electrical engineers and technicians in the fields of the biomedical, computer, and electronics engineering, to master the essential... |
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| SubjectTerms | Computer Hardware Engineering Digital techniques Electronic Devices Electronics & Semiconductors Processors, Memory & Peripherals Signal processing Signal processing -- Digital techniques |
| SubjectTermsDisplay | Electronic books. Signal processing -- Digital techniques. |
| TableOfContents | Title Page
Preface
Table of Contents
1. Introduction to Digital Signal Processing
2. Signal Sampling and Quantization
3. Digital Signals and Systems
4. Discrete Fourier Transform and Signal Spectrum
5. The z-Transform
6. Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations
7. Finite Impulse Response Filter Design
8. Infinite Impulse Response Filter Design
9. Hardware and Software for Digital Signal Processors
10. Adaptive Filters and Applications
11. Waveform Quantization and Compression
12. Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpass Signals
13. Image Processing Basics
Appendices
Bibliography
Answers to Selected Problems
Index
Color Plates Chapter 7 - Finite Impulse Response Filter Design -- 7.1 FINITE IMPULSE RESPONSE FILTER FORMAT -- 7.2 FOURIER TRANSFORM DESIGN -- 7.3 WINDOW METHOD -- 7.4 APPLICATIONS: NOISE REDUCTION AND TWO-BAND DIGITAL CROSSOVER -- 7.5 FREQUENCY SAMPLING DESIGN METHOD -- 7.6 OPTIMAL DESIGN METHOD -- 7.7 REALIZATION STRUCTURES OF FINITE IMPULSE RESPONSE FILTERS -- 7.8 COEFFICIENT ACCURACY EFFECTS ON FINITE IMPULSE RESPONSE FILTERS -- 7.9 SUMMARY OF FIR DESIGN PROCEDURES AND SELECTION OF FIR FILTER DESIGN METHODS IN PRACTICE -- 7.10 SUMMARY -- 7.11 MATLAB PROGRAMS -- 7.12 PROBLEMS -- Chapter 8 - Infinite Impulse Response Filter Design -- 8.1 INFINITE IMPULSE RESPONSE FILTER FORMAT -- 8.2 BILINEAR TRANSFORMATION DESIGN METHOD -- 8.3 DIGITAL BUTTERWORTH AND CHEBYSHEV FILTER DESIGNS -- 8.4 HIGHER-ORDER INFINITE IMPULSE RESPONSE FILTER DESIGN USING THE CASCADE METHOD -- 8.5 APPLICATION: DIGITAL AUDIO EQUALIZER -- 8.6 IMPULSE-INVARIANT DESIGN METHOD -- 8.7 POLE-ZERO PLACEMENT METHOD FOR SIMPLE INFINITE IMPULSE RESPONSE FILTERS -- 8.8 REALIZATION STRUCTURES OF INFINITE IMPULSE RESPONSE FILTERS -- 8.9 APPLICATION: 60-HZ HUM ELIMINATOR AND HEART RATE DETECTION USING ELECTROCARDIOGRAPHY -- 8.10 COEFFICIENT ACCURACY EFFECTS ON INFINITE IMPULSE RESPONSE FILTERS -- 8.11 APPLICATION: GENERATION AND DETECTION OF DTMF TONES USING THE GOERTZEL ALGORITHM -- 8.12 SUMMARY OF INFINITE IMPULSE RESPONSE (IIR) DESIGN PROCEDURES AND SELECTION OF THE IIR FILTER DESIGN METHODS IN PRACTICE -- 8.13 SUMMARY -- 8.14 PROBLEMS -- Chapter 9 - Hardware and Software for Digital Signal Processors -- 9.1 DIGITAL SIGNAL PROCESSOR ARCHITECTURE -- 9.2 DIGITAL SIGNAL PROCESSOR HARDWARE UNITS -- 9.3 DIGITAL SIGNAL PROCESSORS AND MANUFACTURERS -- 9.4 FIXED-POINT AND FLOATING-POINT FORMATS -- 9.5 FINITE IMPULSE RESPONSE AND INFINITE IMPULSE RESPONSE FILTER IMPLEMENTATIONS IN FIXED-POINT SYSTEMS 9.6 DIGITAL SIGNAL PROCESSING PROGRAMMING EXAMPLES -- 9.7 SUMMARY -- 9.8 PROBLEMS -- Chapter 10 - Adaptive Filters and Applications -- 10.1 INTRODUCTION TO LEAST MEAN SQUARE ADAPTIVE FINITE IMPULSE RESPONSE FILTERS -- 10.2 BASIC WIENER FILTER THEORY AND LEAST MEAN SQUARE ALGORITHM -- 10.3 APPLICATIONS: NOISE CANCELLATION, SYSTEM MODELING, AND LINE ENHANCEMENT -- 10.4 OTHER APPLICATION EXAMPLES -- 10.5 LABORATORY EXAMPLES USING THE TMS320C6713 DSK -- 10.6 SUMMARY -- 10.7 PROBLEMS -- Chapter 11 - Waveform Quantization and Compression -- 11.1 LINEAR MIDTREAD QUANTIZATION -- 11.2 μ-LAW COMPANDING -- 11.3 EXAMPLES OF DIFFERENTIAL PULSE CODE MODULATION (DPCM), DELTA MODULATION, AND ADAPTIVE DPCM G.721 -- 11.4 DISCRETE COSINE TRANSFORM, MODIFIED DISCRETE COSINE TRANSFORM, AND TRANSFORM CODING IN MPEG AUDIO -- 11.5 LABORATORY EXAMPLES OF SIGNAL QUANTIZATION USING THE TMS320C6713 DSK -- 11.6 SUMMARY -- 11.7 MATLAB PROGRAMS -- 11.8 PROBLEMS -- Chapter 12 - Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpa ... -- 12.1 MULTIRATE DIGITAL SIGNAL PROCESSING BASICS -- 12.2 POLYPHASE FILTER STRUCTURE AND IMPLEMENTATION -- 12.3 OVERSAMPLING OF ANALOG-TO-DIGITAL CONVERSION -- 12.4 APPLICATION EXAMPLE: CD PLAYER -- 12.5 UNDERSAMPLING OF BANDPASS SIGNALS -- 12.6 Sampling Rate Conversion Using the TMS320C6713 DSK -- 12.7 SUMMARY -- 12.8 PROBLEMS -- Chapter 13 - Subband- and Wavelet-Based Coding -- 13.1 SUBBAND CODING BASICS -- 13.2 SUBBAND DECOMPOSITION AND TWO-CHANNEL PERFECT RECONSTRUCTION QUADRATURE MIRROR FILTER BANK -- 13.3 SUBBAND CODING OF SIGNALS -- 13.4 WAVELET BASICS AND FAMILIES OF WAVELETS -- 13.5 MULTIRESOLUTION EQUATIONS -- 13.6 DISCRETE WAVELET TRANSFORM -- 13.7 WAVELET TRANSFORM CODING OF SIGNALS -- 13.8 MATLAB PROGRAMS -- 13.9 SUMMARY -- 13.10 PROBLEMS -- Chapter 14 - Image Processing Basics Front Cover -- Digital Signal Processing: Fundamentals and Applications -- Copyright -- Contents -- Preface -- Chapter 1 - Introduction to Digital Signal Processing -- 1.1 BASIC CONCEPTS OF DIGITAL SIGNAL PROCESSING -- 1.2 BASIC DIGITAL SIGNAL PROCESSING EXAMPLES IN BLOCK DIAGRAMS -- 1.3 OVERVIEW OF TYPICAL DIGITAL SIGNAL PROCESSING IN REAL-WORLD APPLICATIONS -- 1.4 DIGITAL SIGNAL PROCESSING APPLICATIONS -- 1.5 SUMMARY -- Chapter 2 - Signal Sampling and Quantization -- 2.1 SAMPLING OF CONTINUOUS SIGNAL -- 2.2 SIGNAL RECONSTRUCTION -- 2.3 ANALOG-TO-DIGITAL CONVERSION, DIGITAL-TO-ANALOG CONVERSION, AND QUANTIZATION -- 2.4 SUMMARY -- 2.5 MATLAB PROGRAMS -- Chapter 3 - Digital Signals and Systems -- 3.1 DIGITAL SIGNALS -- 3.2 LINEAR TIME-INVARIANT, CAUSAL SYSTEMS -- 3.3 DIFFERENCE EQUATIONS AND IMPULSE RESPONSES -- 3.4 BOUNDED-IN AND BOUNDED-OUT STABILITY -- 3.5 DIGITAL CONVOLUTION -- 3.6 SUMMARY -- Chapter 4 - Discrete Fourier Transform and Signal Spectrum -- 4.1 DISCRETE FOURIER TRANSFORM -- 4.2 AMPLITUDE SPECTRUM AND POWER SPECTRUM -- 4.3 SPECTRAL ESTIMATION USING WINDOW FUNCTIONS -- 4.4 APPLICATION TO SIGNAL SPECTRAL ESTIMATION -- 4.5 FAST FOURIER TRANSFORM -- 4.6 SUMMARY -- 4.7 PROBLEMS -- Chapter 5 - The z-Transform -- 5.1 DEFINITION -- 5.2 PROPERTIES OF THE Z-TRANSFORM -- 5.3 INVERSE Z-TRANSFORM -- 5.4 SOLUTION OF DIFFERENCE EQUATIONS USING THE Z-TRANSFORM -- 5.5 SUMMARY -- 5.6 PROBLEMS -- Chapter 6 - Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations -- 6.1 THE DIFFERENCE EQUATION AND DIGITAL FILTERING -- 6.2 DIFFERENCE EQUATION AND TRANSFER FUNCTION -- 6.3 THE Z-PLANE POLE-ZERO PLOT AND STABILITY -- 6.4 DIGITAL FILTER FREQUENCY RESPONSE -- 6.5 BASIC TYPES OF FILTERING -- 6.6 REALIZATION OF DIGITAL FILTERS -- 6.7 APPLICATION: SIGNAL ENHANCEMENT AND FILTERING -- 6.8 SUMMARY -- 6.9 PROBLEMS 14.1 IMAGE PROCESSING NOTATION AND DATA FORMATS -- 14.2 IMAGE HISTOGRAM AND EQUALIZATION -- 14.3 IMAGE LEVEL ADJUSTMENT AND CONTRAST -- 14.4 IMAGE FILTERING ENHANCEMENT -- 14.5 IMAGE PSEUDO-COLOR GENERATION AND DETECTION -- 14.6 IMAGE SPECTRA -- 14.7 IMAGE COMPRESSION BY DISCRETE COSINE TRANSFORM -- 14.8 CREATING A VIDEO SEQUENCE BY MIXING TWO IMAGES -- 14.9 VIDEO SIGNAL BASICS -- 14.10 MOTION ESTIMATION IN VIDEO -- 14.11 SUMMARY -- 14.12 PROBLEMS -- Appendix A: Introduction to the MATLAB Environment -- A.1 BASIC COMMANDS AND SYNTAX -- A.2 MATLAB ARRAYS AND INDEXING -- A.3 PLOT UTILITIES: SUBPLOT, PLOT, STEM, AND STAIR -- A.4 MATLAB SCRIPT FILES -- A.5 MATLAB FUNCTIONS -- Appendix B: Review of Analog Signal Processing Basics -- B.1 FOURIER SERIES AND FOURIER TRANSFORM -- B.1.5 FOURIER TRANSFORM -- B.2 LAPLACE TRANSFORM -- B.3 POLES, ZEROS, STABILITY, CONVOLUTION, AND SINUSOIDAL STEADY-STATE RESPONSE -- Appendix C: Normalized Butterworth and Chebyshev Functions -- C.1 NORMALIZED BUTTERWORTH FUNCTION -- C.2 NORMALIZED CHEBYSHEV FUNCTION -- Appendix D: Sinusoidal Steady-State Response of Digital Filters -- D.1 SINUSOIDAL STEADY-STATE RESPONSE -- Appendix E: Finite Impulse Response Filter Design Equations by the Frequency Sampling Design Method -- Appendix F: Wavelet Analysis and Synthesis Equations -- F.1 BASIC PROPERTIES -- F.2 ANALYSIS EQUATIONS -- F.2 WAVELET SYNTHESIS EQUATIONS -- Appendix G: Some Useful Mathematical Formulas -- Answers to Selected Problems -- References -- Index 9.5 Finite Impulse Response and Infinite Impulse Response Filter Implementations in Fixed-Point Systems -- 9.6 Digital Signal Processing Programming Examples -- 9.7 Summary -- 9.8 Problems -- Chapter 10. Adaptive Filters and Applications -- 10.1 Introduction to Least Mean Square Adaptive Finite Impulse Response Filters -- 10.2 Basic Wiener Filter Theor y and Least Mean Square Algorithm -- 10.3 Applications: Noise Cancellation, System Modeling, and Line Enhancement -- 10.4 Other Application Examples -- 10.5 Summary -- 10.6 Problems -- Chapter 11. Waveform Quantization and Compression -- 11.1 Linear Midtread Quantization -- 11.2 m-Law Companding -- 11.3 Examples of Differential Pulse Code Modulation (DPCM), Delta Modulation, and Adaptive DPCM G.721 -- 11.4 Discrete Cosine Transform, Modified Discrete Cosine Transform, and Transform Coding in MPEG Audio -- 11.5 Summary -- 11.6 MATLAB Programs -- 11.7 Problems -- Chapter 12. Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpass Signals -- 12.1 Multirate Digital Signal Processing Basics -- 12.2 Polyphase Filter Structure and Implementation -- 12.3 Oversampling of Analog-to-Digital Conversion -- 12.4 Application Example: CD Player -- 12.5 Undersampling of Bandpass Signals -- 12.6 Summary -- 12.7 Problems -- Chapter 13. Image Processing Basics -- 13.1 Image Processing Notation and Data Formats -- 13.2 Image Histogram and Equalization -- 13.3 Image Level Adjustment and Contrast -- 13.4 Image Filtering Enhancement -- 13.5 Image Pseudo-Color Generation and Detection -- 13.6 Image Spectra -- 13.7 Image Compression by Discrete Cosine Transform -- 13.8 Creating a Video Sequence by Mixing Two Images -- 13.9 Video Signal Basics -- 13.10 Motion Estimation in Video -- 13.11 Summary -- 13.12 Problems -- Appendix A: Introduction to the MATLAB Environment 6.8 Summary -- 6.9 Problems -- Chapter 7. Finite Impulse Response Filter Design -- 7.1 Finite Impulse Response Filter Format -- 7.2 Fourier Transform Design -- 7.3 Window Method -- 7.4 Applications: Noise Reduction and Two-Band Digital Crossover -- 7.5 Frequency Sampling Design Method -- 7.6 Optimal Design Method -- 7.7 Realization Structures of Finite Impulse Response Filters -- 7.8 Coefficient Accuracy Effects on Finite Impulse Response Filters -- 7.9 Summary of Finite Impulse Response (FIR) Design Procedures and Selection of FIR Filter Design Methods in Practice -- 7.10 Summary -- 7.11 MATLAB Programs -- 7.12 Problems -- Chapter 8. Infinite Impulse Response Filter Design -- 8.1 Infinite Impulse Response Filter Format -- 8.2 Bilinear Transformation Design Method -- 8.3 Digital Butterworth and Chebyshev Filter Designs -- 8.4 Higher-Order Infinite Impulse Response Filter Design Using the Cascade Method -- 8.5 Application: Digital Audio Equalizer -- 8.6 Impulse Invariant Design Method -- 8.7 Pole-Zero Placement Method for Simple Infinite Impulse Response Filters -- 8.8 Realization Structures of Infinite Impulse Response Filters -- 8.9 Application: 60-Hz Hum Eliminator and Heart Rate Detection Using Electrocardiography -- 8.10 Coefficient Accuracy Effects on Infinite Impulse Response Filters -- 8.11 Application: Generation and Detection of Dual-Tone Multifrequency Tones Using the Goertzel Algorithm -- 8.12 Summary of Infinite Impulse Response (IIR) Design Procedures and Selection of the IIR Filter Design Methods in Practice -- 8.13 Summary -- 8.14 Problems -- Chapter 9. Hardware and Software for Digital Signal Processors -- 9.1 Digital Signal Processor Architecture -- 9.2 Digital Signal Processor Hardware Units -- 9.3 Digital Signal Processors and Manufacturers -- 9.4 Fixed-Point and Floating-Point Formats A.1 Basic Commands and Syntax -- A.2 MATLAB Array and Indexing -- A.3 Plot Utilities: Subplot, Plot, Stem, and Stair -- A.4 MATLAB Script Files -- A.5 MATLAB Functions -- Appendix B: Review of Analog Signal Processing Basics -- B.1 Fourier Series and Fourier Transform -- B.2 Laplace Transform -- B.3 Poles, Zeros, Stability, Convolution, and Sinusoidal Steady-State Response -- B.4 Problems -- Appendix C: Normalized Butterworth and Chebyshev Functions -- C.1 Normalized Butterworth Function -- C.2 Normalized Chebyshev Function -- Appendix D: Sinusoidal Steady-State Response of Digital Filters -- D.1 Sinusoidal Steady-State Response -- D.2 Properties of the Sinusoidal Steady-State Response -- Appendix E: Finite Impulse Response Filter Design Equations by the Frequency Sampling Design Method -- Appendix F: Some Useful Mathematical Formulas -- Bibliography -- Answers to Selected Problems -- Index Front Cover -- Digital Signal Processing: Fundamentals and Applications -- Copyright Page -- Table of Contents -- Preface -- Chapter 1. Introduction to Digital Signal Processing -- 1.1 Basic Concepts of Digital Signal Processing -- 1.2 Basic Digital Signal Processing Examples in Block Diagrams -- 1.3 Overview of Typical Digital Signal Processing in Real-World Applications -- 1.4 Digital Signal Processing Applications -- 1.5 Summary -- Chapter 2. Signal Sampling and Quantization -- 2.1 Sampling of Continuous Signal -- 2.2 Signal Reconstruction -- 2.3 Analog-to-Digital Conversion, Digital-to-Analog Conversion, and Quantization -- 2.4 Summary -- 2.5 MATLAB Programs -- 2.6 Problems -- Chapter 3. Digital Signals and Systems -- 3.1 Digital Signals -- 3.2 Linear Time-Invariant, Causal Systems -- 3.3 Difference Equations and Impulse Responses -- 3.4 Bounded-in-and-Bounded-out Stability -- 3.5 Digital Convolution -- 3.6 Summary -- 3.7 Problems -- Chapter 4. Discrete Fourier Transform and Signal Spectrum -- 4.1 Discrete Fourier Transform -- 4.2 Amplitude Spectrum and Power Spectrum -- 4.3 Spectral Estimation Using Window Functions -- 4.4 Application to Speech Spectral Estimation -- 4.5 Fast Fourier Transform -- 4.6 Summary -- 4.7 Problems -- Chapter 5. The z-Transform -- 5.1 Definition -- 5.2 Properties of the z-Transform -- 5.3 Inverse z-Transform -- 5.4 Solution of Difference Equations Using the z-Transform -- 5.5 Summary -- 5.6 Problems -- Chapter 6. Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations -- 6.1 The Difference Equation and Digital Filtering -- 6.2 Difference Equation and Transfer Function -- 6.3 The z-Plane Pole-Zero Plot and Stability -- 6.4 Digital Filter Frequency Response -- 6.5 Basic Types of Filtering -- 6.6 Realization of Digital Filters -- 6.7 Application: Speech Enhancement and Filtering |
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