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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| Format: | E-Book |
| Sprache: | Englisch |
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Chantilly
Elsevier
2008
Elsevier Science & Technology Academic Press |
| Ausgabe: | 1 |
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| ISBN: | 0123740908, 9780123740908 |
| Online-Zugang: | Volltext |
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Inhaltsangabe:
- 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
- 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