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E-raamat: Digital Filters: Analysis, Design, and Signal Processing Applications

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  • ISBN-13: 9780071846042
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Digital Filters: Analysis, Design, and Signal Processing ApplicationsSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 02-Feb-2018
  • Kirjastus: McGraw-Hill Inc.,US
  • Keel: eng
  • ISBN-13: 9780071846042
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Up-to-date digital filter design principles, techniques, and applications

Written by a Life Fellow of the IEEE, this comprehensive textbook teaches digital filter design, realization, and implementation and provides detailed illustrations and real-world applications of digital filters to signal processing. Digital Filters: Analysis, Design, and Signal Processing Applications provides a solid foundation in the fundamentals and concepts of DSP and continues with state-of-the-art methodologies and algorithms for the design of digital filters. 

You will get clear explanations of key topics such as spectral analysis, discrete-time systems, and the sampling process. This hands-on resource is supported by a rich collection of online materials which include PDF presentations, detailed solutions of the end-of-chapter problems, MATLAB programs that can be used to analyze and design digital filters of professional quality, and also the authors DSP software D-Filter.

Coverage includes:

Discrete-time systems

The Fourier series and transform

The Z transform

Application of transform theory to systems

The sampling process

The discrete Fourier transform

The window technique

Realization of digital filters

Design of recursive and nonrecursive filters

Approximations for analog filters

Recursive filters satisfying prescribed specifications

Effects of finite word length on digital filters

Design of recursive and nonrecursive filters using optimization methods

Wave digital filters

Signal processing applications































 
Preface xvii
1 Introduction to Digital Signal Processing 1(32)
1.1 Introduction
1(1)
1.2 Signals
1(4)
1.3 Frequency-Domain Representation
5(2)
1.4 Notation
7(1)
1.5 Signal Processing
8(7)
1.6 Analog Filters
15(1)
1.7 Applications of Analog Filters
16(4)
1.8 Digital Filters
20(4)
1.9 Three DSP Applications
24(9)
1.9.1 Processing of EKG Signals
24(1)
1.9.2 Processing of Stock-Exchange Data
24(4)
1.9.3 Processing of DNA and Protein Sequences
28(5)
2 Discrete-Time Systems 33(66)
2.1 Introduction
33(1)
2.2 Basic System Properties
34(7)
2.2.1 Linearity
34(2)
2.2.2 Time Invariance
36(1)
2.2.3 Causality
37(4)
2.3 Characterization of Discrete-Time Systems
41(1)
2.3.1 Nonrecursive Systems
41(1)
2.3.2 Recursive Systems
42(1)
2.4 Discrete-Time System Networks
42(14)
2.4.1 Network Analysis
44(3)
2.4.2 Implementation of Discrete-Time Systems
47(1)
2.4.3 Signal Flow-Graph Analysis
48(8)
2.5 Introduction to Time-Domain Analysis
56(8)
2.6 Convolution Summation
64(8)
2.6.1 Graphical Interpretation
66(5)
2.6.2 Alternative Classification
71(1)
2.7 Stability
72(3)
2.8 State-Space Representation
75(11)
2.8.1 Computability
75(2)
2.8.2 Characterization
77(7)
2.8.3 Time-Domain Analysis
84(1)
2.8.4 Applications of State-Space Method
85(1)
2.9 Problems
86(13)
3 The Fourier Series and Transform 99(70)
3.1 Introduction
99(1)
3.2 Fourier Series
100(15)
3.2.1 Definition
100(1)
3.2.2 Particular Forms
101(5)
3.2.3 Theorems and Properties
106(9)
3.3 Fourier Transform
115(38)
3.3.1 Derivation
116(3)
3.3.2 Particular Forms
119(6)
3.3.3 Theorems and Properties
125(12)
3.3.4 Impulse Functions
137(10)
3.3.5 Generalized Functions
147(1)
3.3.6 Periodic Signals
148(1)
3.3.7 Unit-Step Function
149(4)
3.4 Interrelation between the Fourier Series and the Fourier Transform
153(6)
3.5 Poisson's Summation Formula
159(2)
3.6 Laplace Transform
161(1)
3.7 Problems
161(8)
4 The Z Transform 169(46)
4.1 Introduction
169(1)
4.2 Definition of Z Transform
170(1)
4.3 Convergence Properties
170(3)
4.4 The Z Transform as a Laurent Series
173(1)
4.5 Inverse Z Transform
174(2)
4.6 Additional Theorems and Properties
176(5)
4.7 Z Transforms of Elementary Discrete-Time Signals
181(5)
4.8 Z-Transform Inversion Techniques
186(16)
4.8.1 Use of Binomial Series
189(5)
4.8.2 Use of Partial Fractions
194(4)
4.8.3 Use of Long Division
198(3)
4.8.4 Use of Initial-Value Theorem
201(1)
4.8.5 Use of Real-Convolution Theorem
202(1)
4.9 Spectral Representation of Discrete-Time Signals
202(7)
4.9.1 Frequency Spectrum
202(1)
4.9.2 Periodicity of Frequency Spectrum
203(4)
4.9.3 Interrelations
207(2)
4.10 Problems
209(6)
5 Application of Transform Theory to Systems 215(64)
5.1 Introduction
215(1)
5.2 The Discrete-Time Transfer Function
215(6)
5.2.1 Derivation of H(z) from Difference Equation
216(1)
5.2.2 Derivation of H(z) from System Network
217(1)
5.2.3 Derivation of H(z) from State-Space Characterization
218(3)
5.3 Stability
221(14)
5.3.1 Constraint on Poles
221(3)
5.3.2 Constraint on Eigenvalues
224(3)
5.3.3 Stability Criteria
227(8)
5.4 Time-Domain Analysis
235(2)
5.5 Frequency-Domain Analysis
237(21)
5.5.1 Steady-State Sinusoidal Response
237(2)
5.5.2 Evaluation of Frequency Response
239(1)
5.5.3 Periodicity of Frequency Response
240(1)
5.5.4 Aliasing
241(3)
5.5.5 Frequency Response of Digital Filters
244(14)
5.6 Transfer Functions for Digital Filters
258(7)
5.6.1 First-Order Transfer Function
258(1)
5.6.2 Second-Order Transfer Functions
259(5)
5.6.3 Higher-Order Transfer Functions
264(1)
5.7 Amplitude and Delay Distortion
265(2)
5.8 Continuous-Time Systems
267(5)
5.8.1 The Transfer Function
267(1)
5.8.2 Time-Domain Response
267(3)
5.8.3 Frequency-Domain Analysis
270(2)
5.9 Problems
272(7)
6 The Sampling Process 279(32)
6.1 Introduction
279(1)
6.2 Impulse-Modulated Signals
280(7)
6.2.1 Interrelation between Fourier and Z Transforms
282(2)
6.2.2 Spectral Interrelations between Discrete- and Continuous-Time Signals
284(3)
6.3 The Sampling Theorem
287(2)
6.4 Aliasing
289(1)
6.5 Graphical Representation of Interrelations
290(1)
6.6 Processing of Continuous-Time Signals Using Digital Filters
291(6)
6.7 Practical A/D and D/A Converters
297(5)
6.8 Problems
302(9)
7 The Discrete Fourier Transform 311(42)
7.1 Introduction
311(1)
7.2 Definition
312(1)
7.3 Inverse DFT
312(1)
7.4 Properties
313(3)
7.4.1 Linearity
313(1)
7.4.2 Periodicity
313(1)
7.4.3 Symmetry
313(3)
7.5 Interrelation between the DFT and the Z Transform
316(6)
7.5.1 Time-Domain Aliasing in Discrete-Time Signals
321(1)
7.6 Interrelation between the DFT and the CFT
322(1)
7.6.1 Time-Domain Aliasing in Periodic Discrete-Time Signals
322(1)
7.7 Interrelation between the DFT and the Fourier Series
323(1)
7.8 Simplified Notation
324(1)
7.9 Periodic Convolutions
325(3)
7.9.1 Time-Domain Periodic Convolution
325(3)
7.9.2 Frequency-Domain Periodic Convolution
328(1)
7.10 Fast Fourier-Transform Algorithms
328(14)
7.10.1 Decimation-in-Time Algorithm
328(7)
7.10.2 Decimation-in-Frequency Algorithm
335(6)
7.10.3 Inverse DFT
341(1)
7.11 Application of the FFT Approach to Signal Processing
342(6)
7.11.1 Overlap-and-Add Method
343(2)
7.11.2 Overlap-and-Save Method
345(3)
7.12 Problems
348(5)
8 The Window Technique 353(40)
8.1 Introduction
353(1)
8.2 Basic Principles
353(7)
8.3 Discrete-Time Windows
360(29)
8.3.1 Rectangular Window
363(1)
8.3.2 von Hann and Hamming Windows
364(3)
8.3.3 Blackman Window
367(1)
8.3.4 Dolph-Chebyshev Window
368(2)
8.3.5 Kaiser Window
370(8)
8.3.6 Ultraspherical Window
378(5)
8.3.7 Periodic Discrete-Time Windows
383(2)
8.3.8 Application of Window Technique
385(4)
8.4 Problems
389(4)
9 Realization of Digital Filters 393(36)
9.1 Introduction
393(2)
9.2 Realization
395(20)
9.2.1 Direct Realization
396(5)
9.2.2 Direct Canonic Realization
401(1)
9.2.3 State-Space Realization
402(2)
9.2.4 Lattice Realization
404(4)
9.2.5 Cascade Realization
408(2)
9.2.6 Parallel Realization
410(3)
9.2.7 Transposition
413(2)
9.3 Implementation
415(6)
9.3.1 Design Considerations
415(1)
9.3.2 Systolic Implementations
416(5)
9.4 Problems
421(8)
10 Design of Nonrecursive Filters 429(52)
10.1 Introduction
429(1)
10.2 Properties of Constant-Delay Nonrecursive Filters
430(6)
10.2.1 Impulse Response Symmetries
430(3)
10.2.2 Frequency Response
433(1)
10.2.3 Noncausal Nonrecursive Filters
434(1)
10.2.4 Location of Zeros
435(1)
10.3 Design Using the Fourier Series
436(2)
10.4 Use of Window Technique
438(5)
10.5 Prescribed Filter Specifications
443(26)
10.5.1 Design Procedure Using the Kaiser Window
445(9)
10.5.2 Design Procedure Using the Ultraspherical Window
454(6)
10.5.3 Optimized Design Using the Ultraspherical Window
460(7)
10.5.4 Comparison of Kaiser and Ultraspherical Methods
467(1)
10.5.5 Optimality of Nonrecursive Filters
468(1)
10.6 Design Based on Numerical-Analysis Formulas
469(6)
10.6.1 Design of Digital Differentiators Using Window Method
474(1)
10.7 Problems
475(6)
11 Approximations for Analog Filters 481(46)
11.1 Introduction
481(1)
11.2 Basic Concepts
482(3)
11.2.1 Ideal and Practical Filters
483(1)
11.2.2 Realizability Constraints
484(1)
11.3 Butterworth Approximation
485(7)
11.3.1 Derivation
487(1)
11.3.2 Normalized Transfer Function
487(3)
11.3.3 Minimum Filter Order
490(2)
11.4 Chebyshev Approximation
492(8)
11.4.1 Derivation
493(3)
11.4.2 Normalized Transfer Function
496(2)
11.4.3 Minimum Filter Order
498(2)
11.5 Inverse-Chebyshev Approximation
500(4)
11.5.1 Normalized Transfer Function
501(1)
11.5.2 Minimum Filter Order
502(2)
11.6 Elliptic Approximation
504(6)
11.6.1 Fifth-Order Approximation
505(1)
11.6.2 Minimum Filter Order
506(2)
11.6.3 Normalized Transfer Function
508(2)
11.7 Bessel-Thomson Approximation
510(3)
11.8 Transformations
513(4)
11.8.1 Lowpass-to-Lowpass Transformation
513(1)
11.8.2 Lowpass-to-Bandpass Transformation
513(4)
11.9 Problems
517(10)
12 Design of Recursive Filters 527(34)
12.1 Introduction
527(1)
12.2 Realizability Constraints
527(1)
12.3 Invariant Impulse-Response Method
528(4)
12.4 Modified Invariant Impulse-Response Method
532(4)
12.5 Matched-Z Transformation Method
536(3)
12.6 Bilinear-Transformation Method
539(9)
12.6.1 Derivation
539(3)
12.6.2 Mapping Properties of Bilinear Transformation
542(1)
12.6.3 The Warping Effect
543(5)
12.7 Digital-Filter Transformations
548(5)
12.7.1 General Transformation
548(2)
12.7.2 Lowpass-to-Lowpass Transformation
550(1)
12.7.3 Lowpass-to-Bandstop Transformation
551(2)
12.7.4 Application
553(1)
12.8 Comparison between Recursive and Nonrecursive Designs
553(1)
12.9 Problems
554(7)
13 Recursive Filters Satisfying Prescribed Specifications 561(28)
13.1 Introduction
561(1)
13.2 Design Procedure
562(1)
13.3 Design Formulas
563(12)
13.3.1 Lowpass and Highpass Filters
563(2)
13.3.2 Bandpass and Bandstop Filters
565(5)
13.3.3 Butterworth Filters
570(2)
13.3.4 Chebyshev Filters
572(1)
13.3.5 Inverse-Chebyshev Filters
573(1)
13.3.6 Elliptic Filters
574(1)
13.4 Design Using the Formulas and Tables
575(8)
13.5 Constant Group Delay
583(2)
13.5.1 Delay Equalization
583(1)
13.5.2 Zero-Phase Filters
584(1)
13.6 Amplitude-Response Equalization
585(1)
13.7 Problems
585(4)
14 Effects of Finite Word Length in Digital Filters 589(56)
14.1 Introduction
589(1)
14.2 Number Representation
590(9)
14.2.1 Binary System
590(1)
14.2.2 Fixed-Point Arithmetic
591(4)
14.2.3 Floating-Point Arithmetic
595(2)
14.2.4 Number Quantization
597(2)
14.3 Coefficient Quantization
599(3)
14.4 Low-Sensitivity Structures
602(6)
14.4.1 Case I
605(1)
14.4.2 Case II
606(2)
14.5 Product Quantization
608(8)
14.5.1 Basics of Random Signals
608(4)
14.5.2 Application of Statistical Principles to Digital Filters
612(2)
14.5.3 Noise Analysis
614(2)
14.6 Signal Scaling
616(7)
14.6.1 Method A
617(1)
14.6.2 Method B
618(1)
14.6.3 Types of Scaling
619(2)
14.6.4 Application of Scaling
621(2)
14.7 Minimization of Output Roundoff Noise
623(4)
14.8 Limit-Cycle Oscillations
627(12)
14.8.1 Quantization Limit Cycles
628(3)
14.8.2 Overflow Limit Cycles
631(1)
14.8.3 Elimination of Quantization Limit Cycles
632(5)
14.8.4 Elimination of Overflow Limit Cycles
637(2)
14.9 Problems
639(6)
15 Design of Nonrecursive Filters Using Optimization Methods 645(46)
15.1 Introduction
645(1)
15.2 Problem Formulation
646(4)
15.2.1 Lowpass and Highpass Filters
646(1)
15.2.2 Bandpass and Bandstop Filters
647(2)
15.2.3 Alternation Theorem
649(1)
15.3 Remez Exchange Algorithm
650(5)
15.3.1 Initialization of Extremals
651(1)
15.3.2 Location of Maxima of the Error Function
651(2)
15.3.3 Computation of |E(omega)| and Pc(omega)
653(1)
15.3.4 Rejection of Superfluous Potential Extremals
653(2)
15.3.5 Computation of Impulse Response
655(1)
15.4 Improved Search Methods
655(8)
15.4.1 Selective Step-by-Step Search
655(4)
15.4.2 Cubic Interpolation
659(2)
15.4.3 Quadratic Interpolation
661(1)
15.4.4 Improved Formulation
661(2)
15.5 Efficient Remez Exchange Algorithm
663(3)
15.6 Gradient Information
666(6)
15.7 Prescribed Specifications
672(3)
15.8 Generalization
675(3)
15.8.1 Antisymmetrical Impulse Response and Odd Filter Length
675(2)
15.8.2 Even Filter Length
677(1)
15.9 Digital Differentiators
678(6)
15.9.1 Problem Formulation
679(1)
15.9.2 First Derivative
679(1)
15.9.3 Prescribed Specifications
680(4)
15.10 Arbitrary Amplitude Responses
684(1)
15.11 Multiband Filters
684(2)
15.12 Problems
686(5)
16 Design of Recursive Filters Using Unconstrained Optimization 691(44)
16.1 Introduction
691(1)
16.2 Problem Formulation
692(2)
16.3 Newton's Method
694(3)
16.4 Quasi-Newton Algorithms
697(13)
16.4.1 Basic Quasi-Newton Algorithm
698(3)
16.4.2 Updating Formulas for Matrix Sk+1
701(1)
16.4.3 Inexact Line Searches
701(4)
16.4.4 Practical Quasi-Newton Algorithm
705(5)
16.5 Minimax Algorithms
710(3)
16.6 Improved Minimax Algorithms
713(4)
16.7 Design of Recursive Filters
717(7)
16.7.1 Objective Function
717(1)
16.7.2 Gradient Information
717(1)
16.7.3 Stability
718(1)
16.7.4 Minimum Filter Order
718(1)
16.7.5 Use of Weighting
718(6)
16.8 Design of Recursive Delay Equalizers
724(5)
16.9 Problems
729(6)
17 Design of Recursive Filters Using Constrained Optimization 735(44)
17.1 Introduction
735(2)
17.2 Design Problem
737(2)
17.3 Constrained Optimization Problem
739(11)
17.3.1 Group-Delay Deviation
741(3)
17.3.2 Passband, Transition Band, and Stopband Constraints
744(3)
17.3.3 Stability Constraints
747(1)
17.3.4 Constrained Optimization Problem
748(2)
17.4 Design Procedure
750(16)
17.5 Alternative Initialization Approaches
766(1)
17.6 Comparison of Recursive versus Nonrecursive Digital Filters
767(5)
17.7 Problems
772(7)
18 Wave Digital Filters 779(54)
18.1 Introduction
779(1)
18.2 Sensitivity Considerations
779(2)
18.3 Wave Network Characterization
781(2)
18.4 Element Realizations
783(12)
18.4.1 Impedances
783(1)
18.4.2 Voltage Sources
784(1)
18.4.3 Series Wire Interconnection
785(3)
18.4.4 Parallel Wire Interconnection
788(1)
18.4.5 2-Port Adaptors
788(1)
18.4.6 Transformers
789(1)
18.4.7 Unit Elements
790(3)
18.4.8 Circulators
793(1)
18.4.9 Resonant Circuits
793(2)
18.4.10 Realizability Constraint
795(1)
18.5 Lattice Wave Digital Filters
795(7)
18.5.1 Analysis
795(2)
18.5.2 Alternative Lattice Configuration
797(3)
18.5.3 Digital Realization
800(2)
18.6 Ladder Wave Digital Filters
802(4)
18.7 Filters Satisfying Prescribed Specifications
806(3)
18.8 Frequency-Domain Analysis
809(2)
18.9 Scaling
811(1)
18.10 Elimination of Limit-Cycle Oscillations
812(2)
18.11 Related Synthesis Methods
814(1)
18.12 A Cascade Synthesis Based on the Wave Characterization
815(8)
18.12.1 Generalized-Immittance Converters
815(1)
18.12.2 Analog G-CGIC Configuration
815(2)
18.12.3 Digital G-CGIC Configuration
817(1)
18.12.4 Cascade Synthesis
818(4)
18.12.5 Signal Scaling
822(1)
18.12.6 Output Noise
822(1)
18.13 Choice of Structure
823(2)
18.14 Problems
825(8)
19 Signal Processing Applications 833(46)
19.1 Introduction
833(1)
19.2 Sampling-Frequency Conversion
833(9)
19.2.1 Decimators
834(2)
19.2.2 Interpolators
836(6)
19.2.3 Sampling-Frequency Conversion by a Noninteger Factor
842(1)
19.2.4 Design Considerations
842(1)
19.3 Quadrature-Mirror-Image Filter Banks
842(10)
19.3.1 Operation
843(3)
19.3.2 Elimination of Aliasing Errors
846(3)
19.3.3 Design Considerations
849(3)
19.3.4 Perfect Reconstruction
852(1)
19.4 Hilbert Transformers
852(14)
19.4.1 Design of Hilbert Transformers
856(4)
19.4.2 Single-Sideband Modulation
860(3)
19.4.3 Sampling of Bandpassed Signals
863(3)
19.5 Two-Dimensional Digital Filters
866(7)
19.5.1 Two-Dimensional Convolution
866(1)
19.5.2 Two-Dimensional Z Transform
867(1)
19.5.3 Two-Dimensional Transfer Function
867(1)
19.5.4 Stability
867(2)
19.5.5 Frequency-Domain Analysis
869(2)
19.5.6 Types of 2-D Filters
871(1)
19.5.7 Approximations
872(1)
19.5.8 Applications
873(1)
19.6 Adaptive Digital Filters
873(1)
19.7 Problems
874(5)
Appendix: Complex Analysis 879(32)
A.1 Introduction
879(1)
A.2 Complex Numbers
879(7)
A.2.1 Complex Arithmetic
881(1)
A.2.2 De Moivre's Theorem
882(1)
A.2.3 Euler's Formula
882(1)
A.2.4 Exponential Form
883(1)
A.2.5 Vector Representation
884(1)
A.2.6 Spherical Representation
885(1)
A.3 Functions of a Complex Variable
886(7)
A.3.1 Polynomials
886(1)
A.3.2 Inverse Algebraic Functions
886(1)
A.3.3 Trigonometric Functions and Their Inverses
887(1)
A.3.4 Hyperbolic Functions and Their Inverses
888(1)
A.3.5 Multi-Valued Functions
889(2)
A.3.6 Periodic Functions
891(1)
A.3.7 Rational Algebraic Functions
892(1)
A.4 Basic Principles of Complex Analysis
893(5)
A.4.1 Limit
893(1)
A.4.2 Differentiability
894(1)
A.4.3 Analyticity
894(1)
A.4.4 Zeros
894(1)
A.4.5 Singularities
895(1)
A.4.6 Zero-Pole Plots
896(2)
A.5 Series
898(3)
A.6 Laurent Theorem
901(4)
A.7 Residue Theorem
905(1)
A.8 Analytic Continuation
906(1)
A.9 Conformal Transformations
907(4)
References 911(12)
Index 923
Andreas Antoniou received the B.Sc. (Eng.) and Ph.D. degrees in Electrical Engineering from the University of London, U.K., in 1963 and 1966, respectively, and is a Fellow of the Institution of Electrical Engineers and the Institute of Electrical and Electronics Engineers. He taught at Concordia University from 1970 to 1983 serving as Chair of the Department of Electrical and Computer Engineering during 1977-83. He served as the founding Chair of the Department of Electrical and Computer Engineering, University of Victoria, B.C., Canada, from 1983 to 1990, and is now Professor Emeritus in the same department. His teaching and research interests are in the areas of circuits and systems and digital signal processing. He is the author of Digital Filters: Analysis, Design, and Applications (McGraw-Hill), first and second editions, published in 1978 and 1993, respectively, and the co-author with W.-S Lu of Two-Dimensional Digital Filters (Marcel-Dekker, 1992). Dr. Antoniou served as Associate Editor and Chief Editor for the IEEE Transactions on Circuits and Systems (CAS) during 1983-85 and 1985-87, respectively; as a Distinguished Lecturer of the IEEE Signal Processing Society in 2003; and as the General Chair of the 2004 IEEE International Symposium on Circuits and Systems. He received the Ambrose Fleming Premium for 1964 from the IEE (best paper award), a CAS Golden Jubilee Medal from the IEEE Circuits and Systems Society in 2000, the B.C. Science Council Chairman's Award for Career Achievement for 2000, the Doctor Honoris Causa degree from the Metsovio National Technical University of Athens, Greece, 2002, and the IEEE Circuits and Systems Society Technical Achievements Award for 2005.
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