Digital Signal Processing: Fundamentals and Applications | by Li Tan | ISBN: 9780123740908. Electrical Engineering Books. DSP Applications. Digital Filter Design. Hardware and Software for Digital Signal Processors. Adaptive Filters
Digital Signal Processing: Fundamentals and Applications
by Li Tan
ISBN:9780123740908
Emphasizing achievable results and conclusions through numerous worked examples, while reducing the use of mathematics for an easier grasp of the concepts, this text presents DSP principles, applications and hardware implementation issues.
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Digital Signal Processing—Fundamentals and Applications
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
References
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
References
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
References
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
Reference
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
6.8: Summary
6.9: Problems
Reference
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
References
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
8.33: Bandpass and Bandstop Filter Design Examples
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
References
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
References
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: Summary
10.6: Problems
References
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: Summary
11.6: MATLAB Programs
11.7: Problems
References
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
References
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
Summary
13.12: Problems
References
Appendix A – Introduction to the MATLAB Environment
Overview
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
References
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
References
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
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
Appendix B
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