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Digital Signal Processing
Fundamentals and Applications
- 1st Edition - September 4, 2007
- Author: Li Tan
- Language: English
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 5 5 0 5 7 - 2
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… Read more
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Request a sales quoteThis 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
- End of chapter problems are helpful in ensuring retention and understanding of what was just read
Electrical engineers and technicians designing and building hardware and software for DSP systems
Preface
About the Author
Chapter 1: Introduction to Digital Signal Processing
Objectives
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
Objectives
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
6.8 Summary
6.9 Problems
MATLAB 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
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 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 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
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 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
13.12 Problems
A: Introduction to the MATLAB Environment
B: Review of Analog Signal Processing Basics
C: Normalized Butterworth and Chebyshev Functions
D: Sinusoidal Steady-State Response of Digital Filters
E: Finite Impulse Response Filter Design Equations by the Frequency Sampling Design Method
F: Some Useful Mathematical Formulas
Bibliography
Answers to Selected Problems
Index
- No. of pages: 840
- Language: English
- Edition: 1
- Published: September 4, 2007
- Imprint: Academic Press
- eBook ISBN: 9780080550572
LT
Li Tan
Lizhe Tan is a professor in the Department of Electrical and Computer Engineering at Purdue University Northwest. He received his Ph.D. degree in Electrical Engineering from the University of New Mexico, Albuquerque, in 1992. Dr. Tan has extensively taught signals and systems, digital signal processing, analog and digital control systems, and communication systems for many years. He has published a number of refereed technical articles in journals, conference papers and book chapters in the areas of digital signal processing. He has authored and co-authored 4 textbooks, and holds a US patent. Dr. Tan is a senior member of the IEEE and has served as an associate editor for several engineering journals.
Affiliations and expertise
Professor, Electrical Engineering, Purdue University Northwest, IN, USA