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E-raamat: Digital Signal Processing: Fundamentals and Applications

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(Professor, Electrical Engineering, Purdue University Northwest, IN, USA)
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Digital Signal Processing: Fundamentals and ApplicationsSuurem pilt
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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
  • End of chapter problems are helpful in ensuring retention and understanding of what was just read
Preface xiii
About the Author xvii
Introduction to Digital Signal Processing
1(12)
Basic Concepts of Digital Signal Processing
1(2)
Basic Digital Signal Processing Examples in Block Diagrams
3(3)
Digital Filtering
3(1)
Signal Frequency (Spectrum) Analysis
4(2)
Overview of Typical Digital Signal Processing in Real-World Applications
6(5)
Digital Crossover Audio System
6(1)
Interference Cancellation in Electrocardiography
7(1)
Speech Coding and Compression
7(2)
Compact-Disc Recording System
9(1)
Digital Photo Image Enhancement
10(1)
Digital Signal Processing Applications
11(1)
Summary
12(1)
Signal Sampling and Quantization
13(44)
Sampling of Continuous Signal
13(7)
Signal Reconstruction
20(15)
Practical Considerations for Signal Sampling: Anti-Aliasing Filtering
25(4)
Practical Considerations for Signal Reconstruction: Anti-Image Filter and Equalizer
29(6)
Analog-to-Digital Conversion, Digital-to-Analog Conversion, and Quantization
35(14)
Summary
49(1)
MATLAB Programs
50(1)
Problems
51(6)
Digital Signals and Systems
57(30)
Digital Signals
57(7)
Common Digital Sequences
58(4)
Generation of Digital Signals
62(2)
Linear Time-Invariant, Causal Systems
64(4)
Linearity
64(1)
Time Invariance
65(2)
Causality
67(1)
Difference Equations and Impulse Responses
68(4)
Format of Difference Equation
68(1)
System Representation Using Its Impulse Response
69(3)
Bounded-in-and-Bounded-out Stability
72(2)
Digital Convolution
74(8)
Summary
82(1)
Problems
83(4)
Discrete Fourier Transform and Signal Spectrum
87(48)
Discrete Fourier Transform
87(11)
Fourier Series Coefficients of Periodic Digital Signals
88(4)
Discrete Fourier Transform Formulas
92(6)
Amplitude Spectrum and Power Spectrum
98(12)
Spectral Estimation Using Window Functions
110(7)
Application to Speech Spectral Estimation
117(3)
Fast Fourier Transform
120(11)
Method of Decimation-in-Frequency
121(6)
Method of Decimation-in-Time
127(4)
Summary
131(1)
Problems
131(4)
The z-Transform
135(24)
Definition
135(4)
Properties of the z-Transform
139(3)
Inverse z-Transform
142(9)
Partial Fraction Expansion Using MATLAB
148(3)
Solution of Difference Equations Using the z-Transform
151(4)
Summary
155(1)
Problems
156(3)
Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations
159(56)
The Difference Equation and Digital Filtering
159(6)
Difference Equation and Transfer Function
165(6)
Impulse Response, Step Response, and System Response
169(2)
The z-Plane Pole-Zero Plot and Stability
171(8)
Digital Filter Frequency Response
179(9)
Basic Types of Filtering
188(7)
Realization of Digital Filters
195(7)
Direct-Form I Realization
195(1)
Direct-Form II Realization
196(1)
Cascade (Series) Realization
197(1)
Parallel Realization
198(4)
Application: Speech Enhancement and Filtering
202(6)
Pre-Emphasis of Speech
202(3)
Bandpass Filtering of Speech
205(3)
Summary
208(1)
Problems
209(6)
Finite Impulse Response Filter Design
215(88)
Finite Impulse Response Filter Format
215(2)
Fourier Transform Design
217(12)
Window Method
229(24)
Applications: Noise Reduction and Two-Band Digital Crossover
253(7)
Noise Reduction
253(2)
Speech Noise Reduction
255(1)
Two-Band Digital Crossover
256(4)
Frequency Sampling Design Method
260(8)
Optimal Design Method
268(12)
Realization Structures of Finite Impulse Response Filters
280(3)
Transversal Form
280(2)
Linear Phase Form
282(1)
Coefficient Accuracy Effects on Finite Impulse Response Filters
283(4)
Summary of Finite Impulse Response (FIR) Design Procedures and Selection of FIR Filter Design Methods in Practice
287(3)
Summary
290(1)
MATLAB Programs
291(3)
Problems
294(9)
Infinite Impulse Response Filter Design
303(110)
Infinite Impulse Response Filter Format
303(2)
Bilinear Transformation Design Method
305(17)
Analog Filters Using Lowpass Prototype Transformation
306(4)
Bilinear Transformation and Frequency Warping
310(7)
Bilinear Transformation Design Procedure
317(5)
Digital Butterworth and Chebyshev Filter Designs
322(21)
Lowpass Prototype Function and Its Order
322(4)
Lowpass and Highpass Filter Design Examples
326(10)
Bandpass and Bandstop Filter Design Examples
336(7)
Higher-Order Infinite Impulse Response Filter Design Using the Cascade Method
343(3)
Application: Digital Audio Equalizer
346(4)
Impulse Invariant Design Method
350(8)
Polo-Zero Placement Method for Simple Infinite Impulse Response Filters
358(7)
Second-Order Bandpass Filter Design
359(1)
Second-Order Bandstop (Notch) Filter Design
360(2)
First-Order Lowpass Filter Design
362(2)
First-Order Highpass Filter Design
364(1)
Realization Structures of Infinite Impulse Response Filters
365(5)
Realization of Infinite Impulse Response Filters in Direct-Form I and Direct-Form II
366(2)
Realization of Higher-Order Infinite Impulse Response Filters via the Cascade Form
368(2)
Application: 60-Hz Hum Eliminator and Heart Rate Detection Using Electrocardiography
370(7)
Coefficient Accuracy Effects on Infinite Impulse Response Filters
377(4)
Application: Generation and Detection of Dual-Tone Multifrequency Tones Using Goertzel Algorithm
381(15)
Single-Tone Generator
382(2)
Dual-Tone Multifrequency Tone Generator
384(2)
Goertzel Algorithm
386(5)
Dual-Tone Multifrequency Tone Detection Using the Modified Goertzel Algorithm
391(5)
Summary of Infinite Impulse Response (IIR) Design Procedures and Selection of the IIR Filter Design Methods in Practice
396(5)
Summary
401(1)
Problems
402(11)
Hardware and Software for Digital Signal Processors
413(50)
Digital Signal Processor Architecture
413(3)
Digital Signal Processor Hardware Units
416(3)
Multiplier and Accumulator
416(1)
Shifters
417(1)
Address Generators
418(1)
Digital Signal Processors and Manufactures
419(1)
Fixed-Point and Floating-Point Formats
420(21)
Fixed-Point Format
420(9)
Floating-Point Format
429(5)
IEEE Floating-Point Formats
434(3)
Fixed-Point Digital Signal Processors
437(2)
Floating-Point Processors
439(2)
Finite Impulse Response and Infinite Impulse Response Filter Implementation in Fixed-Point Systems
441(6)
Digital Signal Processing Programming Examples
447(13)
Overview of TMS320C67x DSK
447(4)
Concept of Real-Time Processing
451(1)
Linear Buffering
452(3)
Sample C Programs
455(5)
Summary
460(1)
Problems
461(2)
Adaptive Filters and Applications
463(34)
Introduction to Least Mean Square Adaptive Finite Impulse Response Filters
463(4)
Basic Wiener Filter Theory and Least Mean Square Algorithm
467(6)
Applications: Noise Cancellation, System Modeling, and Line Enhancement
473(13)
Noise Cancellation
473(6)
System Modeling
479(5)
Line Enhancement Using Linear Prediction
484(2)
Other Application Examples
486(5)
Canceling Periodic Interferences Using Linear Prediction
487(1)
Electrocardiography Interference Cancellation
488(1)
Echo Cancellation in Long-Distance Telephone Circuits
489(2)
Summary
491(1)
Problems
491(6)
Waveform Quantization and Compression
497(60)
Linear Midtread Quantization
497(4)
μ-law Companding
501(9)
Analog μ-Law Companding
501(5)
Digital μ-Law Companding
506(4)
Examples of Differential Pulse Code Modulation (DPCM), Delta Modulation, and Adaptive DPCM G.721
510(12)
Examples of Differential Pulse Code Modulation and Delta Modulation
510(5)
Adaptive Differential Pulse Code Modulation G.721
515(7)
Discrete Cosine Transform, Modified Discrete Cosine Transform, and Transform Coding in MPEG Audio
522(11)
Discrete Cosine Transform
522(3)
Modified Discrete Cosine Transform
525(5)
Transform Coding in MPEG Audio
530(3)
Summary
533(1)
MATLAB Programs
534(16)
Problems
550(7)
Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpass Signals
557(60)
Multirate Digital Signal Processing Basics
557(26)
Sampling Rate Reduction by an Integer Factor
558(6)
Sampling Rate Increase by an Integer Factor
564(6)
Changing Sampling Rate by a Non-Integer Factor L/M
570(5)
Application: CD Audio Player
575(3)
Multistage Decimation
578(5)
Polyphase Filter Structure and Implementation
583(6)
Oversampling of Analog-to-Digital Conversion
589(10)
Oversampling and Analog-to-Digital Conversion Resolution
590(3)
Sigma-Delta Modulation Analog-to-Digital Conversion
593(6)
Application Example: CD Player
599(2)
Undersampling of Bandpass Signals
601(8)
Summary
609(1)
Problems
610(7)
Image Processing Basics
617(82)
Image Processing Notation and Data Formats
617(8)
8-Bit Gray Level Images
618(1)
24-Bit Color Images
619(1)
8-Bit Color Images
620(1)
Intensity Images
621(1)
Red, Green, Blue Components and Grayscale Conversion
622(2)
MATLAB Functions for Format Conversion
624(1)
Image Histogram and Equalization
625(12)
Grayscale Histogram and Equalization
625(7)
24-Bit Color Image Equalization
632(1)
8-Bit Indexed Color Image Equalization
633(3)
MATLAB Functions for Equalization
636(1)
Image Level Adjustment and Contrast
637(5)
Linear Level Adjustment
638(3)
Adjusting the Level for Display
641(1)
Matlab Functions for Image Level Adjustment
642(1)
Image Filtering Enhancement
642(15)
Lowpass Noise Filtering
643(3)
Median Filtering
646(5)
Edge Detection
651(4)
MATLAB Functions for Image Filtering
655(2)
Image Pseudo-Color Generation and Detection
657(4)
Image Spectra
661(3)
Image Compression by Discrete Cosine Transform
664(13)
Two-Dimensional Discrete Cosine Transform
666(3)
Two-Dimensional JPEG Grayscale Image Compression Example
669(2)
JPEG Color Image Compression
671(6)
Creating a Video Sequence by Mixing Two Images
677(1)
Video Signal Basics
677(10)
Analog Video
678(7)
Digital Video
685(2)
Motion Estimation in Video
687(3)
Summary
690(2)
Problems
692(7)
Appendix A Introduction to the MATLAB Environment
699(10)
Basic Commands and Syntax
699(4)
MATLAB Array and Indexing
703(1)
Plot Utilities: Subplot, Plot, Stem, and Stair
704(1)
MATLAB Script Files
704(1)
MATLAB Functions
705(4)
Appendix B Review of Analog Signal Processing Basics
709(32)
Fourier Series and Fourier Transform
709(17)
Sine-Cosine Form
709(1)
Amplitude-Phase Form
710(1)
Complex Exponential Form
711(3)
Spectral Plots
714(7)
Fourier Transform
721(5)
Laplace Transform
726(5)
Laplace Transform and Its Table
726(1)
Solving Differential Equations Using Laplace Transform
727(3)
Transfer Function
730(1)
Poles, Zeros, Stability, Convolution, and Sinusoidal Steady-State Response
731(5)
Poles, Zeros, and Stability
731(2)
Convolution
733(2)
Sinusoidal Steady-State Response
735(1)
Problems
736(5)
Appendix C Normalized Butterworth and Chebyshev Fucntions
741(8)
Normalized Butterworth Function
741(3)
Normalized Chebyshev Function
744(5)
Appendix D Sinusoidal Steady-State Response of Digital Filters
749(4)
Sinusoidal Steady-State Response
749(2)
Properties of the Sinusoidal Steady-State Response
751(2)
Appendix E Finite Impulse Response Filter Design Equations by the Frequency Sampling Design Method
753(4)
Appendix F Some Useful Mathematical Formulas
757(4)
Bibliography 761(4)
Answers to Selected Problems 765(26)
Index 791


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.
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