Digital signal processing: [principles, algorithms, and applications]
A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer scienc...
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Upper Saddle River, NJ
Prentice Hall
2007
|
| Edition: | 4. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Summary: | A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing. |
| Physical Description: | XIX, 1084 S. Ill., graph. Darst. |
| ISBN: | 0131873741 9780131873742 |
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| 245 | 1 | 0 | |a Digital signal processing |b [principles, algorithms, and applications] |c John G. Proakis ; Dimitris G. Manolakis |
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| 264 | 1 | |a Upper Saddle River, NJ |b Prentice Hall |c 2007 | |
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| 520 | 3 | |a A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing. | |
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| 700 | 1 | |a Manolakis, Dimitris G. |e Verfasser |0 (DE-588)1050810430 |4 aut | |
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| _version_ | 1804136220934012928 |
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| adam_text | DIGITAL SIGNAL PROCESSING FOURTH EDITION JOHN G. PROAKIS DEPARTMENT OF
ELECTRICAL AND COMPUTER ENGINEERING NORTHEASTERN UNIVERSITY BOSTON,
MASSACHUSETTS DIMITRIS G. MANOLAKIS MIT LINCOLN LABORATORY LEXINGTON,
MASSACHUSETTS PEARSON PRENTICE HALL UPPER SADDLE RIVER, NEW JERSEY 07458
CONTENTS PREFACE XVII 1 INTRODUCTION 1 1.1 SIGNALS, SYSTEMS, AND SIGNAL
PROCESSING 2 1.1.1 BASIC ELEMENTS OF A DIGITAL SIGNAL PROCESSING SYSTEM
4 1.1.2 ADVANTAGES OF DIGITAL OVER ANALOG SIGNAL PROCESSING 5 1.2
CLASSIFICATION OF SIGNALS 6 1.2.1 MULTICHANNEL AND MULTIDIMENSIONAL
SIGNALS 6 1.2.2 CONTINUOUS-TIME VERSUS DISCRETE-TIME SIGNALS 9 1.2.3
CONTINUOUS-VALUED VERSUS DISCRETE-VALUED SIGNALS 10 1.2.4 DETERMINISTIC
VERSUS RANDOM SIGNALS 11 1.3 THE CONCEPT OF FREQUENCY IN CONTINUOUS-TIME
AND DISCRETE-TIME SIGNALS 12 1.3.1 CONTINUOUS-TIME SINUSOIDAL SIGNALS 12
1.3.2 DISCRETE-TIME SINUSOIDAL SIGNALS 14 1.3.3 HARMONICALLY RELATED
COMPLEX EXPONENTIALS 17 1.4 ANALOG-TO-DIGITAL AND DIGITAL-TO-ANALOG
CONVERSION 19 1.4.1 SAMPLING OF ANALOG SIGNALS 21 1.4.2 THE SAMPLING
THEOREM 26 1.4.3 QUANTIZATION OF CONTINUOUS-AMPLITUDE SIGNALS 31 1.4.4
QUANTIZATION OF SINUSOIDAL SIGNALS 34 1.4.5 CODING OF QUANTIZED SAMPLES
35 1.4.6 DIGITAL-TO-ANALOG CONVERSION 36 1.4.7 ANALYSIS OF DIGITAL
SIGNALS AND SYSTEMS VERSUS DISCRETE-TIME SIGNALS 36 AND SYSTEMS 1.5
SUMMARY AND REFERENCES 37 PROBLEMS 37 VI CONTENTS 2 DISCRETE-TIME
SIGNALS AND SYSTEMS 41 2.1 DISCRETE-TIME SIGNALS 42 2.1.1 SOME
ELEMENTARY DISCRETE-TIME SIGNALS 43 2.1.2 CLASSIFICATION OF
DISCRETE-TIME SIGNALS 45 2.1.3 SIMPLE MANIPULATIONS OF DISCRETE-TIME
SIGNALS 50 2.2 DISCRETE-TIME SYSTEMS 53 2.2.1 INPUT-OUTPUT DESCRIPTION
OF SYSTEMS 54 2.2.2 BLOCK DIAGRAM REPRESENTATION OF DISCRETE-TIME
SYSTEMS 57 2.2.3 CLASSIFICATION OF DISCRETE-TIME SYSTEMS 59 2.2.4
INTERCONNECTION OF DISCRETE-TIME SYSTEMS 67 2.3 ANALYSIS OF
DISCRETE-TIME LINEAR TIME-INVARIANT SYSTEMS 69 2.3.1 TECHNIQUES FOR THE
ANALYSIS OF LINEAR SYSTEMS 69 2.3.2 RESOLUTION OF A DISCRETE-TIME SIGNAL
INTO IMPULSES 71 2.3.3 RESPONSE OF LTI SYSTEMS TO ARBITRARY INPUTS: THE
CONVOLUTION SUM 73 2.3.4 PROPERTIES OF CONVOLUTION AND THE
INTERCONNECTION OF LTI SYSTEMS 80 2.3.5 CAUSAL LINEAR TIME-INVARIANT
SYSTEMS 83 2.3.6 STABILITY OF LINEAR TIME-INVARIANT SYSTEMS 85 2.3.7
SYSTEMS WITH FINITE-DURATION AND INFINITE-DURATION IMPULSE 88 RESPONSE
2.4 DISCRETE-TIME SYSTEMS DESCRIBED BY DIFFERENCE EQUATIONS 89 2.4.1
RECURSIVE AND NONRECURSIVE DISCRETE-TIME SYSTEMS 90 2.4.2 LINEAR
TIME-INVARIANT SYSTEMS CHARACTERIZED BY 93 CONSTANT-COEFFICIENT
DIFFERENCE EQUATIONS 2.4.3 SOLUTION OF LINEAR CONSTANT-COEFFICIENT
DIFFERENCE EQUATIONS 98 2.4.4 THE IMPULSE RESPONSE OF A LINEAR
TIME-INVARIANT RECURSIVE SYSTEM 106 2.5 IMPLEMENTATION OF DISCRETE-TIME
SYSTEMS 109 2.5.1 STRUCTURES FOR THE REALIZATION OF LINEAR
TIME-INVARIANT SYSTEMS 109 2.5.2 RECURSIVE AND NONRECURSIVE REALIZATIONS
OF FIR SYSTEMS 113 2.6 CORRELATION OF DISCRETE-TIME SIGNALS 116 2.6.1
CROSSCORRELATION AND AUTOCORRELATION SEQUENCES 118 2.6.2 PROPERTIES OF
THE AUTOCORRELATION AND CROSSCORRELATION SEQUENCES 120 2.6.3 CORRELATION
OF PERIODIC SEQUENCES 123 2.6.4 INPUT-OUTPUT CORRELATION SEQUENCES 125
2.7 SUMMARY AND REFERENCES 128 PROBLEMS 129 CONTENTS VII THE Z
-TRANSFORM AND ITS APPLICATION TO THE ANALYSIS OF LTI 147 SYSTEMS 3.1
THE Z-TRANSFORM 147 3.1.1 THE DIRECT Z-TRANSFORM 147 3.1.2 THE INVERSE Z
-TRANSFORM 156 3.2 PROPERTIES OF THE Z-TRANSFORM 157 3.3 RATIONAL
Z-TRANSFORMS 170 3.3.1 POLES AND ZEROS 170 3.3.2 POLE LOCATION AND
TIME-DOMAIN BEHAVIOR FOR CAUSAL SIGNALS 174 3.3.3 THE SYSTEM FUNCTION OF
A LINEAR TIME-INVARIANT SYSTEM 177 3.4 INVERSION OF THE Z-TRANSFORM 180
3.4.1 THE INVERSE Z-TRANSFORM BY CONTOUR INTEGRATION 180 3.4.2 THE
INVERSE Z-TRANSFORM BY POWER SERIES EXPANSION 182 3.4.3 THE INVERSE
Z-TRANSFORM BY PARTIAL-FRACTION EXPANSION 184 3.4.4 DECOMPOSITION OF
RATIONAL Z-TRANSFORMS 192 3.5 ANALYSIS OF LINEAR TIME-INVARIANT SYSTEMS
IN THE Z-DOMAIN 193 3.5.1 RESPONSE OF SYSTEMS WITH RATIONAL SYSTEM
FUNCTIONS 194 3.5.2 TRANSIENT AND STEADY-STATE RESPONSES 195 3.5.3
CAUSALITY AND STABILITY 196 3.5.4 POLE-ZERO CANCELLATIONS 198 3.5.5
MULTIPLE-ORDER POLES AND STABILITY 200 3.5.6 STABILITY OF SECOND-ORDER
SYSTEMS 201 3.6 THE ONE-SIDED Z-TRANSFORM 205 3.6.1 DEFINITION AND
PROPERTIES 206 3.6.2 SOLUTION OF DIFFERENCE EQUATIONS 210 3.6.3 RESPONSE
OF POLE-ZERO SYSTEMS WITH NONZERO INITIAL CONDITIONS 211 3.7 SUMMARY AND
REFERENCES 214 PROBLEMS 214 FREQUENCY ANALYSIS OF SIGNALS 224 4.1
FREQUENCY ANALYSIS OF CONTINUOUS-TIME SIGNALS 225 4.1.1 THE FOURIER
SERIES FOR CONTINUOUS-TIME PERIODIC SIGNALS 226 4.1.2 POWER DENSITY
SPECTRUM OF PERIODIC SIGNALS 230 4.1.3 THE FOURIER TRANSFORM FOR
CONTINUOUS-TIME APERIODIC SIGNALS 234 4.1.4 ENERGY DENSITY SPECTRUM OF
APERIODIC SIGNALS 238 VIII CONTENTS 4.2 FREQUENCY ANALYSIS OF
DISCRETE-TIME SIGNALS 241 4.2.1 THE FOURIER SERIES FOR DISCRETE-TIME
PERIODIC SIGNALS 241 4.2.2 POWER DENSITY SPECTRUM OF PERIODIC SIGNALS
245 4.2.3 THE FOURIER TRANSFORM OF DISCRETE-TIME APERIODIC SIGNALS 248
4.2.4 CONVERGENCE OF THE FOURIER TRANSFORM 251 4.2.5 ENERGY DENSITY
SPECTRUM OF APERIODIC SIGNALS 254 4.2.6 RELATIONSHIP OF THE FOURIER
TRANSFORM TO THE Z-TRANSFORM 259 4.2.7 /THE CEPSTRUM 261 4.2.8 *THE
FOURIER TRANSFORM OF SIGNALS WITH POLES ON THE UNIT CIRCLE 262 4.2.9
FREQUENCY-DOMAIN CLASSIFICATION OF SIGNALS: THE CONCEPT OF 265 BANDWIDTH
4.2.10 THE FREQUENCY RANGES OF SOME NATURAL SIGNALS 267 4.3
FREQUENCY-DOMAIN AND TIME-DOMAIN SIGNAL PROPERTIES 268 4.4 PROPERTIES OF
THE FOURIER TRANSFORM FOR DISCRETE-TIME SIGNALS 271 4.4.1 SYMMETRY
PROPERTIES OF THE FOURIER TRANSFORM 272 4.4.2 FOURIER TRANSFORM THEOREMS
AND PROPERTIES 279 4.5 SUMMARY AND REFERENCES 291 PROBLEMS 292 5
FREQUENCY-DOMAIN ANALYSIS OF LTI SYSTEMS 300 5.1 FREQUENCY-DOMAIN
CHARACTERISTICS OF LINEAR TIME-INVARIANT SYSTEMS 300 5.1.1 RESPONSE TO
COMPLEX EXPONENTIAL AND SINUSOIDAL SIGNALS: THE 301 FREQUENCY RESPONSE
FUNCTION 5.1.2 STEADY-STATE AND TRANSIENT RESPONSE TO SINUSOIDAL INPUT
SIGNALS 310 5.1.3 STEADY-STATE RESPONSE TO PERIODIC INPUT SIGNALS 311
5.1.4 RESPONSE TO APERIODIC INPUT SIGNALS 312 5.2 FREQUENCY RESPONSE OF
LTI SYSTEMS 314 5.2.1 FREQUENCY RESPONSE OF A SYSTEM WITH A RATIONAL
SYSTEM FUNCTION 314 5.2.2 COMPUTATION OF THE FREQUENCY RESPONSE FUNCTION
317 5.3 CORRELATION FUNCTIONS AND SPECTRA AT THE OUTPUT OF LTI SYSTEMS
321 5.3.1 INPUT-OUTPUT CORRELATION FUNCTIONS AND SPECTRA 322 5.3.2
CORRELATION FUNCTIONS AND POWER SPECTRA FOR RANDOM INPUT SIGNALS 323 5.4
LINEAR TIME-INVARIANT SYSTEMS AS FREQUENCY-SELECTIVE FILTERS 326 5.4.1
IDEAL FILTER CHARACTERISTICS 327 5.4.2 LOWPASS, HIGHPASS, AND BANDPASS
FILTERS 329 5.4.3 DIGITAL RESONATORS 335 5.4.4 NOTCH FILTERS 339 5.4.5
COMB FILTERS 341 CONTENTS IX 5.4.6 ALL-PASS FILTERS 345 5.4.7 DIGITAL
SINUSOIDAL OSCILLATORS 347 5.5 INVERSE SYSTEMS AND DECONVOLUTION 349
5.5.1 INVERTIBILITY OF LINEAR TIME-INVARIANT SYSTEMS 350 5.5.2
MINIMUM-PHASE, MAXIMUM-PHASE, AND MIXED-PHASE SYSTEMS 354 5.5.3 SYSTEM
IDENTIFICATION AND DECONVOLUTION 358 5.5.4 HOMOMORPHIC DECONVOLUTION 360
5.6 SUMMARY AND REFERENCES 362 PROBLEMS 363 6 SAMPLING AND
RECONSTRUCTION OF SIGNALS 384 6.1 IDEAL SAMPLING AND RECONSTRUCTION OF
CONTINUOUS-TIME SIGNALS 384 6.2 DISCRETE-TIME PROCESSING OF
CONTINUOUS-TIME SIGNALS 395 6.3 ANALOG-TO-DIGITAL AND DIGITAL-TO-ANALOG
CONVERTERS 401 6.3.1 ANALOG-TO-DIGITAL CONVERTERS 401 6.3.2 QUANTIZATION
AND CODING 403 6.3.3 ANALYSIS OF QUANTIZATION ERRORS 406 6.3.4
DIGITAL-TO-ANALOG CONVERTERS 408 6.4 SAMPLING AND RECONSTRUCTION OF
CONTINUOUS-TIME BANDPASS SIGNALS 410 6.4.1 UNIFORM OR FIRST-ORDER
SAMPLING 411 6.4.2 INTERLEAVED OR NONUNIFORM SECOND-ORDER SAMPLING 416
6.4.3 BANDPASS SIGNAL REPRESENTATIONS 422 6.4.4 SAMPLING USING BANDPASS
SIGNAL REPRESENTATIONS 426 6.5 SAMPLING OF DISCRETE-TIME SIGNALS 427
6.5.1 SAMPLING AND INTERPOLATION OF DISCRETE-TIME SIGNALS 427 6.5.2
REPRESENTATION AND SAMPLING OF BANDPASS DISCRETE-TIME SIGNALS 430 6.6
OVERSAMPLING A/D AND D/A CONVERTERS 433 6.6.1 OVERSAMPLING A/D
CONVERTERS 433 6.6.2 OVERSAMPLING D/A CONVERTERS 439 6.7 SUMMARY AND
REFERENCES 440 PROBLEMS 440 X CONTENTS 7 THE DISCRETE FOURIER TRANSFORM:
ITS PROPERTIES AND APPLICATIONS 449 7.1 FREQUENCY-DOMAIN SAMPLING: THE
DISCRETE FOURIER TRANSFORM 449 7.1.1 FREQUENCY-DOMAIN SAMPLING AND
RECONSTRUCTION OF DISCRETE-TIME 449 SIGNALS 7.1.2 THE DISCRETE FOURIER
TRANSFORM (DFT) 454 7.1.3 THE DFT AS A LINEAR TRANSFORMATION 459 7.1.4
^RELATIONSHIP OF THE DFT TO OTHER TRANSFORMS 461 7.2 PROPERTIES OF THE
DFT 464 7.2.1 PERIODICITY, LINEARITY, AND SYMMETRY PROPERTIES 465 7.2.2
MULTIPLICATION OF TWO DFTS AND CIRCULAR CONVOLUTION 471 7.2.3 ADDITIONAL
DFT PROPERTIES 476 7.3 LINEAR FILTERING METHODS BASED ON THE DFT 480
7.3.1 USE OF THE DFT IN LINEAR FILTERING 481 7.3.2 FILTERING OF LONG
DATA SEQUENCES 485 7.4 FREQUENCY ANALYSIS OF SIGNALS USING THE DFT 488
7.5 THE DISCRETE COSINE TRANSFORM 495 7.5.1 FORWARD DCT 495 7.5.2
INVERSE DCT 497 7.5.3 DCT AS AN ORTHOGONAL TRANSFORM 498 7.6 SUMMARY AND
REFERENCES 501 PROBLEMS 502 8 EFFICIENT COMPUTATION OF THE DFT: FAST
FOURIER TRANSFORM 511 ALGORITHMS 8.1 EFFICIENT COMPUTATION OF THE DFT:
FFT ALGORITHMS 511 8.1.1 DIRECT COMPUTATION OF THE DFT 512 8.1.2
DIVIDE-AND-CONQUER APPROACH TO COMPUTATION OF THE DFT 513 8.1.3 RADIX-2
FFT ALGORITHMS 519 8.1.4 RADIX-4 FFT ALGORITHMS 527 8.1.5 SPLIT-RADIX
FFT ALGORITHMS 532 8.1.6 IMPLEMENTATION OF FFT ALGORITHMS 536 8.2
APPLICATIONS OF FFT ALGORITHMS 538 8.2.1 EFFICIENT COMPUTATION OF THE
DFT OF TWO REAL SEQUENCES 538 8.2.2 EFFICIENT COMPUTATION OF THE DFT OF
A 2 N -POINT REAL SEQUENCE 539 8.2.3 USE OF THE FFT ALGORITHM IN LINEAR
FILTERING AND CORRELATION 540 CONTENTS XI 8.3 A LINEAR FILTERING
APPROACH TO COMPUTATION OF THE DFT 542 8.3.1 THE GOERTZEL ALGORITHM 542
8.3.2 THE CHIRP-Z TRANSFORM ALGORITHM 544 8.4 QUANTIZATION EFFECTS IN
THE COMPUTATION OF THE DFT 549 8.4.1 QUANTIZATION ERRORS IN THE DIRECT
COMPUTATION OF THE DFT 549 8.4.2 QUANTIZATION ERRORS IN FFT ALGORITHMS
552 8.5 SUMMARY AND REFERENCES 555 PROBLEMS 556 9 IMPLEMENTATION OF
DISCRETE-TIME SYSTEMS 563 9.1 STRUCTURES FOR THE REALIZATION OF
DISCRETE-TIME SYSTEMS 563 9.2 STRUCTURES FOR FIR SYSTEMS 565 9.2.1
DIRECT-FORM STRUCTURE 566 9.2.2 CASCADE-FORM STRUCTURES 567 9.2.3
FREQUENCY-SAMPLING STRUCTURES 569 9.2.4 LATTICE STRUCTURE 574 9.3
STRUCTURES FOR MR SYSTEMS 582 9.3.1 DIRECT-FORM STRUCTURES 582 9.3.2
SIGNAL FLOW GRAPHS AND TRANSPOSED STRUCTURES 585 9.3.3 CASCADE-FORM
STRUCTURES 589 9.3.4 PARALLEL-FORM STRUCTURES 591 9.3.5 LATTICE AND
LATTICE-LADDER STRUCTURES FOR IIR SYSTEMS 594 9.4 REPRESENTATION OF
NUMBERS 601 9.4.1 FIXED-POINT REPRESENTATION OF NUMBERS 601 9.4.2 BINARY
FLOATING-POINT REPRESENTATION OF NUMBERS 605 9.4.3 ERRORS RESULTING FROM
ROUNDING AND TRUNCATION 608 9.5 QUANTIZATION OF FILTER COEFFICIENTS 613
9.5.1 ANALYSIS OF SENSITIVITY TO QUANTIZATION OF FILTER COEFFICIENTS 613
9.5.2 QUANTIZATION OF COEFFICIENTS IN FIR FILTERS 620 9.6 ROUND-OFF
EFFECTS IN DIGITAL FILTERS 624 9.6.1 LIMIT-CYCLE OSCILLATIONS IN
RECURSIVE SYSTEMS 624 9.6.2 SCALING TO PREVENT OVERFLOW 629 9.6.3
STATISTICAL CHARACTERIZATION OF QUANTIZATION EFFECTS IN FIXED-POINT 631
REALIZATIONS OF DIGITAL FILTERS 9.7 SUMMARY AND REFERENCES 640 PROBLEMS
641 XII CONTENTS 10 DESIGN OF DIGITAL FILTERS 654 10.1 GENERAL
CONSIDERATIONS 654 10.1.1 CAUSALITY AND ITS IMPLICATIONS 655 10.1.2
CHARACTERISTICS OF PRACTICAL FREQUENCY-SELECTIVE FILTERS 659 10.2 DESIGN
OF FIR FILTERS 660 10.2.1 SYMMETRIC AND ANTISYMMETRIC FIR FILTERS 660
10.2.2 /DESIGN OF LINEAR-PHASE FIR FILTERS USING WINDOWS 664 10.2.3
DESIGN OF LINEAR-PHASE FIR FILTERS BY THE FREQUENCY-SAMPLING 671 METHOD
10.2.4 DESIGN OF OPTIMUM EQUIRIPPLE LINEAR-PHASE FIR FILTERS 678 10.2.5
DESIGN OF FIR DIFFERENTIATORS 691 10.2.6 DESIGN OF HILBERT TRANSFORMERS
693 10.2.7 COMPARISON OF DESIGN METHODS FOR LINEAR-PHASE FIR FILTERS 700
10.3 DESIGN OF MR FILTERS FROM ANALOG FILTERS 701 10.3.1 IIR FILTER
DESIGN BY APPROXIMATION OF DERIVATIVES 703 10.3.2 IIR FILTER DESIGN BY
IMPULSE INVARIANCE 707 10.3.3 IIR FILTER DESIGN BY THE BILINEAR
TRANSFORMATION 712 10.3.4 CHARACTERISTICS OF COMMONLY USED ANALOG
FILTERS 717 10.3.5 SOME EXAMPLES OF DIGITAL FILTER DESIGNS BASED ON THE
BILINEAR 727 TRANSFORMATION 10.4 FREQUENCY TRANSFORMATIONS 730 10.4.1
FREQUENCY TRANSFORMATIONS IN THE ANALOG DOMAIN 730 10.4.2 FREQUENCY
TRANSFORMATIONS IN THE DIGITAL DOMAIN 732 10.5 SUMMARY AND REFERENCES
734 PROBLEMS 735 11 MULTIRATE DIGITAL SIGNAL PROCESSING 750 11.1
INTRODUCTION 751 11.2 DECIMATION BY A FACTOR D 755 11.3 INTERPOLATION BY
A FACTOR / 760 11.4 SAMPLING RATE CONVERSION BY A RATIONAL FACTOR I / D
762 11.5 IMPLEMENTATION OF SAMPLING RATE CONVERSION 766 11.5.1 POLYPHASE
FILTER STRUCTURES 766 11.5.2 INTERCHANGE OF FILTERS AND
DOWNSAMPLERS/UPSAMPLERS 767 11.5.3 SAMPLING RATE CONVERSION WITH
CASCADED INTEGRATOR COMB FILTERS 769 11.5.4 POLYPHASE STRUCTURES FOR
DECIMATION AND INTERPOLATION FILTERS 771 11.5.5 STRUCTURES FOR RATIONAL
SAMPLING RATE CONVERSION 774 CONTENTS XIII 11.6 MULTISTAGE
IMPLEMENTATION OF SAMPLING RATE CONVERSION 775 11.7 SAMPLING RATE
CONVERSION OF BANDPASS SIGNALS 779 11.8 SAMPLING RATE CONVERSION BY AN
ARBITRARY FACTOR 781 11.8.1 ARBITRARY RESAMPLING WITH POLYPHASE
INTERPOLATORS 782 11.8.2 ARBITRARY RESAMPLING WITH FARROW FILTER
STRUCTURES 782 11.9 APPLICATIONS OF MULTIRATE SIGNAL PROCESSING 784
11.9.1 DESIGN OF PHASE SHIFTERS 784 11.9.2 INTERFACING OF DIGITAL
SYSTEMS WITH DIFFERENT SAMPLING RATES 785 11.9.3 IMPLEMENTATION OF
NARROWBAND LOWPASS FILTERS 786 11.9.4 SUBBAND CODING OF SPEECH SIGNALS
787 11.10 DIGITAL FILTER BANKS 790 11.10.1 POLYPHASE STRUCTURES OF
UNIFORM FILTER BANKS 794 11.10.2 TRANSMULTIPLEXERS 796 11.11 TWO-CHANNEL
QUADRATURE MIRROR FILTER BANK 798 11.11.1 ELIMINATION OF ALIASING 799
11.11.2 CONDITION FOR PERFECT RECONSTRUCTION 801 11.11.3 POLYPHASE FORM
OF THE QMF BANK 801 11.11.4 LINEAR PHASE FIR QMF BANK 802 11.11.5 IIR
QMF BANK 803 11.11.6 PERFECT RECONSTRUCTION TWO-CHANNEL FIR QMF BANK 803
11.11.7 TWO-CHANNEL QMF BANKS IN SUBBAND CODING 806 11.12 M-CHANNEL QMF
BANK 807 11.12.1 ALIAS-FREE AND PERFECT RECONSTRUCTION CONDITION 808
11.12.2 POLYPHASE FORM OF THE M -CHANNEL QMF BANK 808 11.13 SUMMARY AND
REFERENCES 813 PROBLEMS 813 12 LINEAR PREDICTION AND OPTIMUM LINEAR
FILTERS 823 12.1 RANDOM SIGNALS, CORRELATION FUNCTIONS, AND POWER
SPECTRA 823 12.1.1 RANDOM PROCESSES 824 12.1.2 STATIONARY RANDOM
PROCESSES 825 12.1.3 STATISTICAL (ENSEMBLE) AVERAGES 825 12.1.4
STATISTICAL AVERAGES FOR JOINT RANDOM PROCESSES 826 12.1.5 POWER DENSITY
SPECTRUM 828 12.1.6 DISCRETE-TIME RANDOM SIGNALS 829 12.1.7 TIME
AVERAGES FOR A DISCRETE-TIME RANDOM PROCESS 830 12.1.8 MEAN-ERGODIC
PROCESS 831 12.1.9 CORRELATION-ERGODIC PROCESSES 832 XIV CONTENTS 12.2
INNOVATIONS REPRESENTATION OF A STATIONARY RANDOM PROCESS 834 12.2.1
RATIONAL POWER SPECTRA 836 12.2.2 RELATIONSHIPS BETWEEN THE FILTER
PARAMETERS AND THE 837 AUTOCORRELATION SEQUENCE 12.3 FORWARD AND
BACKWARD LINEAR PREDICTION 838 12.3.1 FORWARD LINEAR PREDICTION 839
12.3.2 BACKWARD LINEAR PREDICTION 841 12.3.3 * THE OPTIMUM REFLECTION
COEFFICIENTS FOR THE LATTICE FORWARD AND 845 * BACKWARD PREDICTORS
12.3.4 RELATIONSHIP OF AN AR PROCESS TO LINEAR PREDICTION 846 12.4
SOLUTION OF THE NORMAL EQUATIONS 846 12.4.1 THE LEVINSON-DURBIN
ALGORITHM 847 12.4.2 THE SCHUR ALGORITHM 850 12.5 PROPERTIES OF THE
LINEAR PREDICTION-ERROR FILTERS 855 12.6 AR LATTICE AND ARMA
LATTICE-LADDER FILTERS 858 12.6.1 AR LATTICE STRUCTURE 858 12.6.2 ARMA
PROCESSES AND LATTICE-LADDER FILTERS 860 12.7 WIENER FILTERS FOR
FILTERING AND PREDICTION 863 12.7.1 FIR WIENER FILTER 864 12.7.2
ORTHOGONALITY PRINCIPLE IN LINEAR MEAN-SQUARE ESTIMATION 866 12.7.3 IIR
WIENER FILTER 867 12.7.4 NONCAUSAL WIENER FILTER 872 12.8 SUMMARY AND
REFERENCES 873 PROBLEMS 874 13 ADAPTIVE FILTERS 880 13.1 APPLICATIONS OF
ADAPTIVE FILTERS 880 13.1.1 SYSTEM IDENTIFICATION OR SYSTEM MODELING 882
13.1.2 ADAPTIVE CHANNEL EQUALIZATION 883 13.1.3 ECHO CANCELLATION IN
DATA TRANSMISSION OVER TELEPHONE CHANNELS 887 13.1.4 SUPPRESSION OF
NARROWBAND INTERFERENCE IN A WIDEBAND SIGNAL 891 13.1.5 ADAPTIVE LINE
ENHANCER 895 13.1.6 ADAPTIVE NOISE CANCELLING 896 13.1.7 LINEAR
PREDICTIVE CODING OF SPEECH SIGNALS 897 13.1.8 ADAPTIVE ARRAYS 900 13.2
ADAPTIVE DIRECT-FORM FIR FILTERS*THE LMS ALGORITHM 902 13.2.1 MINIMUM
MEAN-SQUARE-ERROR CRITERION 903 13.2.2 THE LMS ALGORITHM 905 CONTENTS XV
13.2.3 RELATED STOCHASTIC GRADIENT ALGORITHMS 907 13.2.4 PROPERTIES OF
THE LMS ALGORITHM 909 13.3 ADAPTIVE DIRECT-FORM FILTERS*RLS ALGORITHMS
916 13.3.1 RLS ALGORITHM 916 13.3.2 THE LDU FACTORIZATION AND
SQUARE-ROOT ALGORITHMS 921 13.3.3 FAST RLS ALGORITHMS 923 13.3.4
PROPERTIES OF THE DIRECT-FORM RLS ALGORITHMS 925 13.4 ADAPTIVE
LATTICE-LADDER FILTERS 927 13.4.1 RECURSIVE LEAST-SQUARES LATTICE-LADDER
ALGORITHMS 928 13.4.2 OTHER LATTICE ALGORITHMS 949 13.4.3 PROPERTIES OF
LATTICE-LADDER ALGORITHMS 950 13.5 SUMMARY AND REFERENCES 954 PROBLEMS
955 14 POWER SPECTRUM ESTIMATION 960 14.1 ESTIMATION OF SPECTRA FROM
FINITE-DURATION OBSERVATIONS OF SIGNALS 961 14.1.1 COMPUTATION OF THE
ENERGY DENSITY SPECTRUM 961 14.1.2 ESTIMATION OF THE AUTOCORRELATION AND
POWER SPECTRUM OF RANDOM 966 SIGNALS: THE PERIODOGRAM 14.1.3 THE USE OF
THE DFT IN POWER SPECTRUM ESTIMATION 971 14.2 NONPARAMETRIC METHODS FOR
POWER SPECTRUM ESTIMATION 974 14.2.1 THE BARTLETT METHOD: AVERAGING
PERIODOGRAMS 974 14.2.2 THE WELCH METHOD: AVERAGING MODIFIED
PERIODOGRAMS 975 14.2.3 THE BLACKMAN AND TUKEY METHOD: SMOOTHING THE
PERIODOGRAM 978 14.2.4 PERFORMANCE CHARACTERISTICS OF NONPARAMETRIC
POWER SPECTRUM 981 ESTIMATORS 14.2.5 COMPUTATIONAL REQUIREMENTS OF
NONPARAMETRIC POWER SPECTRUM 984 ESTIMATES 14.3 PARAMETRIC METHODS FOR
POWER SPECTRUM ESTIMATION 986 14.3.1 RELATIONSHIPS BETWEEN THE
AUTOCORRELATION AND THE MODEL 988 PARAMETERS 14.3.2 THE YULE-WALKER
METHOD FOR THE AR MODEL PARAMETERS 990 14.3.3 THE BURG METHOD FOR THE AR
MODEL PARAMETERS 991 14.3.4 UNCONSTRAINED LEAST-SQUARES METHOD FOR THE
AR MODEL 994 PARAMETERS 14.3.5 SEQUENTIAL ESTIMATION METHODS FOR THE AR
MODEL PARAMETERS 995 14.3.6 SELECTION OF AR MODEL ORDER 996 14.3.7 MA
MODEL FOR POWER SPECTRUM ESTIMATION 997 14.3.8 ARMA MODEL FOR POWER
SPECTRUM ESTIMATION 999 14.3.9 SOME EXPERIMENTAL RESULTS 1001 XVI
CONTENTS 14.4 FILTER BANK METHODS 1009 14.4.1 FILTER BANK REALIZATION OF
THE PERIODOGRAM 1010 14.4.2 MINIMUM VARIANCE SPECTRAL ESTIMATES 1012
14.5 EIGENANALYSIS ALGORITHMS FOR SPECTRUM ESTIMATION 1015 14.5.1
PISARENKO HARMONIC DECOMPOSITION METHOD 1017 14.5.2 EIGEN-DECOMPOSITION
OF THE AUTOCORRELATION MATRIX FOR SINUSOIDS IN 1019 WHITE NOISE 14.5.3
|MUSIC ALGORITHM 1021 14.5.4 ESPRIT ALGORITHM 1022 14.5.5 ORDER
SELECTION CRITERIA 1025 14.5.6 EXPERIMENTAL RESULTS 1026 14.6 SUMMARY
AND REFERENCES 1029 PROBLEMS 1030 A RANDOM NUMBER GENERATORS 1041 B
TABLES OF TRANSITION COEFFICIENTS FOR THE DESIGN OF LINEAR-PHASE 1047
FIR FILTERS REFERENCES AND BIBLIOGRAPHY 1053 ANSWERS TO SELECTED
PROBLEMS 1067 INDEX 1077
|
| adam_txt |
DIGITAL SIGNAL PROCESSING FOURTH EDITION JOHN G. PROAKIS DEPARTMENT OF
ELECTRICAL AND COMPUTER ENGINEERING NORTHEASTERN UNIVERSITY BOSTON,
MASSACHUSETTS DIMITRIS G. MANOLAKIS MIT LINCOLN LABORATORY LEXINGTON,
MASSACHUSETTS PEARSON PRENTICE HALL UPPER SADDLE RIVER, NEW JERSEY 07458
CONTENTS PREFACE XVII 1 INTRODUCTION 1 1.1 SIGNALS, SYSTEMS, AND SIGNAL
PROCESSING 2 1.1.1 BASIC ELEMENTS OF A DIGITAL SIGNAL PROCESSING SYSTEM
4 1.1.2 ADVANTAGES OF DIGITAL OVER ANALOG SIGNAL PROCESSING 5 1.2
CLASSIFICATION OF SIGNALS 6 1.2.1 MULTICHANNEL AND MULTIDIMENSIONAL
SIGNALS 6 1.2.2 CONTINUOUS-TIME VERSUS DISCRETE-TIME SIGNALS 9 1.2.3
CONTINUOUS-VALUED VERSUS DISCRETE-VALUED SIGNALS 10 1.2.4 DETERMINISTIC
VERSUS RANDOM SIGNALS 11 1.3 THE CONCEPT OF FREQUENCY IN CONTINUOUS-TIME
AND DISCRETE-TIME SIGNALS 12 1.3.1 CONTINUOUS-TIME SINUSOIDAL SIGNALS 12
1.3.2 DISCRETE-TIME SINUSOIDAL SIGNALS 14 1.3.3 HARMONICALLY RELATED
COMPLEX EXPONENTIALS 17 1.4 ANALOG-TO-DIGITAL AND DIGITAL-TO-ANALOG
CONVERSION 19 1.4.1 SAMPLING OF ANALOG SIGNALS 21 1.4.2 THE SAMPLING
THEOREM 26 1.4.3 QUANTIZATION OF CONTINUOUS-AMPLITUDE SIGNALS 31 1.4.4
QUANTIZATION OF SINUSOIDAL SIGNALS 34 1.4.5 CODING OF QUANTIZED SAMPLES
35 1.4.6 DIGITAL-TO-ANALOG CONVERSION 36 1.4.7 ANALYSIS OF DIGITAL
SIGNALS AND SYSTEMS VERSUS DISCRETE-TIME SIGNALS 36 AND SYSTEMS 1.5
SUMMARY AND REFERENCES 37 PROBLEMS 37 VI CONTENTS 2 DISCRETE-TIME
SIGNALS AND SYSTEMS 41 2.1 DISCRETE-TIME SIGNALS 42 2.1.1 SOME
ELEMENTARY DISCRETE-TIME SIGNALS 43 2.1.2 CLASSIFICATION OF
DISCRETE-TIME SIGNALS 45 2.1.3 SIMPLE MANIPULATIONS OF DISCRETE-TIME
SIGNALS 50 2.2 DISCRETE-TIME SYSTEMS 53 2.2.1 INPUT-OUTPUT DESCRIPTION
OF SYSTEMS 54 2.2.2 BLOCK DIAGRAM REPRESENTATION OF DISCRETE-TIME
SYSTEMS 57 2.2.3 CLASSIFICATION OF DISCRETE-TIME SYSTEMS 59 2.2.4
INTERCONNECTION OF DISCRETE-TIME SYSTEMS 67 2.3 ANALYSIS OF
DISCRETE-TIME LINEAR TIME-INVARIANT SYSTEMS 69 2.3.1 TECHNIQUES FOR THE
ANALYSIS OF LINEAR SYSTEMS 69 2.3.2 RESOLUTION OF A DISCRETE-TIME SIGNAL
INTO IMPULSES 71 2.3.3 RESPONSE OF LTI SYSTEMS TO ARBITRARY INPUTS: THE
CONVOLUTION SUM 73 2.3.4 PROPERTIES OF CONVOLUTION AND THE
INTERCONNECTION OF LTI SYSTEMS 80 2.3.5 CAUSAL LINEAR TIME-INVARIANT
SYSTEMS 83 2.3.6 STABILITY OF LINEAR TIME-INVARIANT SYSTEMS 85 2.3.7
SYSTEMS WITH FINITE-DURATION AND INFINITE-DURATION IMPULSE 88 RESPONSE
2.4 DISCRETE-TIME SYSTEMS DESCRIBED BY DIFFERENCE EQUATIONS 89 2.4.1
RECURSIVE AND NONRECURSIVE DISCRETE-TIME SYSTEMS 90 2.4.2 LINEAR
TIME-INVARIANT SYSTEMS CHARACTERIZED BY 93 CONSTANT-COEFFICIENT
DIFFERENCE EQUATIONS 2.4.3 SOLUTION OF LINEAR CONSTANT-COEFFICIENT
DIFFERENCE EQUATIONS 98 2.4.4 THE IMPULSE RESPONSE OF A LINEAR
TIME-INVARIANT RECURSIVE SYSTEM 106 2.5 IMPLEMENTATION OF DISCRETE-TIME
SYSTEMS 109 2.5.1 STRUCTURES FOR THE REALIZATION OF LINEAR
TIME-INVARIANT SYSTEMS 109 2.5.2 RECURSIVE AND NONRECURSIVE REALIZATIONS
OF FIR SYSTEMS 113 2.6 CORRELATION OF DISCRETE-TIME SIGNALS 116 2.6.1
CROSSCORRELATION AND AUTOCORRELATION SEQUENCES 118 2.6.2 PROPERTIES OF
THE AUTOCORRELATION AND CROSSCORRELATION SEQUENCES 120 2.6.3 CORRELATION
OF PERIODIC SEQUENCES 123 2.6.4 INPUT-OUTPUT CORRELATION SEQUENCES 125
2.7 SUMMARY AND REFERENCES 128 PROBLEMS 129 CONTENTS VII THE Z
-TRANSFORM AND ITS APPLICATION TO THE ANALYSIS OF LTI 147 SYSTEMS 3.1
THE Z-TRANSFORM 147 3.1.1 THE DIRECT Z-TRANSFORM 147 3.1.2 THE INVERSE Z
-TRANSFORM 156 3.2 PROPERTIES OF THE Z-TRANSFORM 157 3.3 RATIONAL
Z-TRANSFORMS 170 3.3.1 POLES AND ZEROS 170 3.3.2 POLE LOCATION AND
TIME-DOMAIN BEHAVIOR FOR CAUSAL SIGNALS 174 3.3.3 THE SYSTEM FUNCTION OF
A LINEAR TIME-INVARIANT SYSTEM 177 3.4 INVERSION OF THE Z-TRANSFORM 180
3.4.1 THE INVERSE Z-TRANSFORM BY CONTOUR INTEGRATION 180 3.4.2 THE
INVERSE Z-TRANSFORM BY POWER SERIES EXPANSION 182 3.4.3 THE INVERSE
Z-TRANSFORM BY PARTIAL-FRACTION EXPANSION 184 3.4.4 DECOMPOSITION OF
RATIONAL Z-TRANSFORMS 192 3.5 ANALYSIS OF LINEAR TIME-INVARIANT SYSTEMS
IN THE Z-DOMAIN 193 3.5.1 RESPONSE OF SYSTEMS WITH RATIONAL SYSTEM
FUNCTIONS 194 3.5.2 TRANSIENT AND STEADY-STATE RESPONSES 195 3.5.3
CAUSALITY AND STABILITY 196 3.5.4 POLE-ZERO CANCELLATIONS 198 3.5.5
MULTIPLE-ORDER POLES AND STABILITY 200 3.5.6 STABILITY OF SECOND-ORDER
SYSTEMS 201 3.6 THE ONE-SIDED Z-TRANSFORM 205 3.6.1 DEFINITION AND
PROPERTIES 206 3.6.2 SOLUTION OF DIFFERENCE EQUATIONS 210 3.6.3 RESPONSE
OF POLE-ZERO SYSTEMS WITH NONZERO INITIAL CONDITIONS 211 3.7 SUMMARY AND
REFERENCES 214 PROBLEMS 214 FREQUENCY ANALYSIS OF SIGNALS 224 4.1
FREQUENCY ANALYSIS OF CONTINUOUS-TIME SIGNALS 225 4.1.1 THE FOURIER
SERIES FOR CONTINUOUS-TIME PERIODIC SIGNALS 226 4.1.2 POWER DENSITY
SPECTRUM OF PERIODIC SIGNALS 230 4.1.3 THE FOURIER TRANSFORM FOR
CONTINUOUS-TIME APERIODIC SIGNALS 234 4.1.4 ENERGY DENSITY SPECTRUM OF
APERIODIC SIGNALS 238 VIII CONTENTS 4.2 FREQUENCY ANALYSIS OF
DISCRETE-TIME SIGNALS 241 4.2.1 THE FOURIER SERIES FOR DISCRETE-TIME
PERIODIC SIGNALS 241 4.2.2 POWER DENSITY SPECTRUM OF PERIODIC SIGNALS
245 4.2.3 THE FOURIER TRANSFORM OF DISCRETE-TIME APERIODIC SIGNALS 248
4.2.4 CONVERGENCE OF THE FOURIER TRANSFORM 251 4.2.5 ENERGY DENSITY
SPECTRUM OF APERIODIC SIGNALS 254 4.2.6 RELATIONSHIP OF THE FOURIER
TRANSFORM TO THE Z-TRANSFORM 259 4.2.7 /THE CEPSTRUM 261 4.2.8 *THE
FOURIER TRANSFORM OF SIGNALS WITH POLES ON THE UNIT CIRCLE 262 4.2.9
FREQUENCY-DOMAIN CLASSIFICATION OF SIGNALS: THE CONCEPT OF 265 BANDWIDTH
4.2.10 THE FREQUENCY RANGES OF SOME NATURAL SIGNALS 267 4.3
FREQUENCY-DOMAIN AND TIME-DOMAIN SIGNAL PROPERTIES 268 4.4 PROPERTIES OF
THE FOURIER TRANSFORM FOR DISCRETE-TIME SIGNALS 271 4.4.1 SYMMETRY
PROPERTIES OF THE FOURIER TRANSFORM 272 4.4.2 FOURIER TRANSFORM THEOREMS
AND PROPERTIES 279 4.5 SUMMARY AND REFERENCES 291 PROBLEMS 292 5
FREQUENCY-DOMAIN ANALYSIS OF LTI SYSTEMS 300 5.1 FREQUENCY-DOMAIN
CHARACTERISTICS OF LINEAR TIME-INVARIANT SYSTEMS 300 5.1.1 RESPONSE TO
COMPLEX EXPONENTIAL AND SINUSOIDAL SIGNALS: THE 301 FREQUENCY RESPONSE
FUNCTION 5.1.2 STEADY-STATE AND TRANSIENT RESPONSE TO SINUSOIDAL INPUT
SIGNALS 310 5.1.3 STEADY-STATE RESPONSE TO PERIODIC INPUT SIGNALS 311
5.1.4 RESPONSE TO APERIODIC INPUT SIGNALS 312 5.2 FREQUENCY RESPONSE OF
LTI SYSTEMS 314 5.2.1 FREQUENCY RESPONSE OF A SYSTEM WITH A RATIONAL
SYSTEM FUNCTION 314 5.2.2 COMPUTATION OF THE FREQUENCY RESPONSE FUNCTION
317 5.3 CORRELATION FUNCTIONS AND SPECTRA AT THE OUTPUT OF LTI SYSTEMS
321 5.3.1 INPUT-OUTPUT CORRELATION FUNCTIONS AND SPECTRA 322 5.3.2
CORRELATION FUNCTIONS AND POWER SPECTRA FOR RANDOM INPUT SIGNALS 323 5.4
LINEAR TIME-INVARIANT SYSTEMS AS FREQUENCY-SELECTIVE FILTERS 326 5.4.1
IDEAL FILTER CHARACTERISTICS 327 5.4.2 LOWPASS, HIGHPASS, AND BANDPASS
FILTERS 329 5.4.3 DIGITAL RESONATORS 335 5.4.4 NOTCH FILTERS 339 5.4.5
COMB FILTERS 341 CONTENTS IX 5.4.6 ALL-PASS FILTERS 345 5.4.7 DIGITAL
SINUSOIDAL OSCILLATORS 347 5.5 INVERSE SYSTEMS AND DECONVOLUTION 349
5.5.1 INVERTIBILITY OF LINEAR TIME-INVARIANT SYSTEMS 350 5.5.2
MINIMUM-PHASE, MAXIMUM-PHASE, AND MIXED-PHASE SYSTEMS 354 5.5.3 SYSTEM
IDENTIFICATION AND DECONVOLUTION 358 5.5.4 HOMOMORPHIC DECONVOLUTION 360
5.6 SUMMARY AND REFERENCES 362 PROBLEMS 363 6 SAMPLING AND
RECONSTRUCTION OF SIGNALS 384 6.1 IDEAL SAMPLING AND RECONSTRUCTION OF
CONTINUOUS-TIME SIGNALS 384 6.2 DISCRETE-TIME PROCESSING OF
CONTINUOUS-TIME SIGNALS 395 6.3 ANALOG-TO-DIGITAL AND DIGITAL-TO-ANALOG
CONVERTERS 401 6.3.1 ANALOG-TO-DIGITAL CONVERTERS 401 6.3.2 QUANTIZATION
AND CODING 403 6.3.3 ANALYSIS OF QUANTIZATION ERRORS 406 6.3.4
DIGITAL-TO-ANALOG CONVERTERS 408 6.4 SAMPLING AND RECONSTRUCTION OF
CONTINUOUS-TIME BANDPASS SIGNALS 410 6.4.1 UNIFORM OR FIRST-ORDER
SAMPLING 411 6.4.2 INTERLEAVED OR NONUNIFORM SECOND-ORDER SAMPLING 416
6.4.3 BANDPASS SIGNAL REPRESENTATIONS 422 6.4.4 SAMPLING USING BANDPASS
SIGNAL REPRESENTATIONS 426 6.5 SAMPLING OF DISCRETE-TIME SIGNALS 427
6.5.1 SAMPLING AND INTERPOLATION OF DISCRETE-TIME SIGNALS 427 6.5.2
REPRESENTATION AND SAMPLING OF BANDPASS DISCRETE-TIME SIGNALS 430 6.6
OVERSAMPLING A/D AND D/A CONVERTERS 433 6.6.1 OVERSAMPLING A/D
CONVERTERS 433 6.6.2 OVERSAMPLING D/A CONVERTERS 439 6.7 SUMMARY AND
REFERENCES 440 PROBLEMS 440 X CONTENTS 7 THE DISCRETE FOURIER TRANSFORM:
ITS PROPERTIES AND APPLICATIONS 449 7.1 FREQUENCY-DOMAIN SAMPLING: THE
DISCRETE FOURIER TRANSFORM 449 7.1.1 FREQUENCY-DOMAIN SAMPLING AND
RECONSTRUCTION OF DISCRETE-TIME 449 SIGNALS 7.1.2 THE DISCRETE FOURIER
TRANSFORM (DFT) 454 7.1.3 THE DFT AS A LINEAR TRANSFORMATION 459 7.1.4
^RELATIONSHIP OF THE DFT TO OTHER TRANSFORMS 461 7.2 PROPERTIES OF THE
DFT 464 7.2.1 PERIODICITY, LINEARITY, AND SYMMETRY PROPERTIES 465 7.2.2
MULTIPLICATION OF TWO DFTS AND CIRCULAR CONVOLUTION 471 7.2.3 ADDITIONAL
DFT PROPERTIES 476 7.3 LINEAR FILTERING METHODS BASED ON THE DFT 480
7.3.1 USE OF THE DFT IN LINEAR FILTERING 481 7.3.2 FILTERING OF LONG
DATA SEQUENCES 485 7.4 FREQUENCY ANALYSIS OF SIGNALS USING THE DFT 488
7.5 THE DISCRETE COSINE TRANSFORM 495 7.5.1 FORWARD DCT 495 7.5.2
INVERSE DCT 497 7.5.3 DCT AS AN ORTHOGONAL TRANSFORM 498 7.6 SUMMARY AND
REFERENCES 501 PROBLEMS 502 8 EFFICIENT COMPUTATION OF THE DFT: FAST
FOURIER TRANSFORM 511 ALGORITHMS 8.1 EFFICIENT COMPUTATION OF THE DFT:
FFT ALGORITHMS 511 8.1.1 DIRECT COMPUTATION OF THE DFT 512 8.1.2
DIVIDE-AND-CONQUER APPROACH TO COMPUTATION OF THE DFT 513 8.1.3 RADIX-2
FFT ALGORITHMS 519 8.1.4 RADIX-4 FFT ALGORITHMS 527 8.1.5 SPLIT-RADIX
FFT ALGORITHMS 532 8.1.6 IMPLEMENTATION OF FFT ALGORITHMS 536 8.2
APPLICATIONS OF FFT ALGORITHMS 538 8.2.1 EFFICIENT COMPUTATION OF THE
DFT OF TWO REAL SEQUENCES 538 8.2.2 EFFICIENT COMPUTATION OF THE DFT OF
A 2 N -POINT REAL SEQUENCE 539 8.2.3 USE OF THE FFT ALGORITHM IN LINEAR
FILTERING AND CORRELATION 540 CONTENTS XI 8.3 A LINEAR FILTERING
APPROACH TO COMPUTATION OF THE DFT 542 8.3.1 THE GOERTZEL ALGORITHM 542
8.3.2 THE CHIRP-Z TRANSFORM ALGORITHM 544 8.4 QUANTIZATION EFFECTS IN
THE COMPUTATION OF THE DFT 549 8.4.1 QUANTIZATION ERRORS IN THE DIRECT
COMPUTATION OF THE DFT 549 8.4.2 QUANTIZATION ERRORS IN FFT ALGORITHMS
552 8.5 SUMMARY AND REFERENCES 555 PROBLEMS 556 9 IMPLEMENTATION OF
DISCRETE-TIME SYSTEMS 563 9.1 STRUCTURES FOR THE REALIZATION OF
DISCRETE-TIME SYSTEMS 563 9.2 STRUCTURES FOR FIR SYSTEMS 565 9.2.1
DIRECT-FORM STRUCTURE 566 9.2.2 CASCADE-FORM STRUCTURES 567 9.2.3
FREQUENCY-SAMPLING STRUCTURES 569 9.2.4 LATTICE STRUCTURE 574 9.3
STRUCTURES FOR MR SYSTEMS 582 9.3.1 DIRECT-FORM STRUCTURES 582 9.3.2
SIGNAL FLOW GRAPHS AND TRANSPOSED STRUCTURES 585 9.3.3 CASCADE-FORM
STRUCTURES 589 9.3.4 PARALLEL-FORM STRUCTURES 591 9.3.5 LATTICE AND
LATTICE-LADDER STRUCTURES FOR IIR SYSTEMS 594 9.4 REPRESENTATION OF
NUMBERS 601 9.4.1 FIXED-POINT REPRESENTATION OF NUMBERS 601 9.4.2 BINARY
FLOATING-POINT REPRESENTATION OF NUMBERS 605 9.4.3 ERRORS RESULTING FROM
ROUNDING AND TRUNCATION 608 9.5 QUANTIZATION OF FILTER COEFFICIENTS 613
9.5.1 ANALYSIS OF SENSITIVITY TO QUANTIZATION OF FILTER COEFFICIENTS 613
9.5.2 QUANTIZATION OF COEFFICIENTS IN FIR FILTERS 620 9.6 ROUND-OFF
EFFECTS IN DIGITAL FILTERS 624 9.6.1 LIMIT-CYCLE OSCILLATIONS IN
RECURSIVE SYSTEMS 624 9.6.2 SCALING TO PREVENT OVERFLOW 629 9.6.3
STATISTICAL CHARACTERIZATION OF QUANTIZATION EFFECTS IN FIXED-POINT 631
REALIZATIONS OF DIGITAL FILTERS 9.7 SUMMARY AND REFERENCES 640 PROBLEMS
641 XII CONTENTS 10 DESIGN OF DIGITAL FILTERS 654 10.1 GENERAL
CONSIDERATIONS 654 10.1.1 CAUSALITY AND ITS IMPLICATIONS 655 10.1.2
CHARACTERISTICS OF PRACTICAL FREQUENCY-SELECTIVE FILTERS 659 10.2 DESIGN
OF FIR FILTERS 660 10.2.1 SYMMETRIC AND ANTISYMMETRIC FIR FILTERS 660
10.2.2 /DESIGN OF LINEAR-PHASE FIR FILTERS USING WINDOWS 664 10.2.3
DESIGN OF LINEAR-PHASE FIR FILTERS BY THE FREQUENCY-SAMPLING 671 METHOD
10.2.4 DESIGN OF OPTIMUM EQUIRIPPLE LINEAR-PHASE FIR FILTERS 678 10.2.5
DESIGN OF FIR DIFFERENTIATORS 691 10.2.6 DESIGN OF HILBERT TRANSFORMERS
693 10.2.7 COMPARISON OF DESIGN METHODS FOR LINEAR-PHASE FIR FILTERS 700
10.3 DESIGN OF MR FILTERS FROM ANALOG FILTERS 701 10.3.1 IIR FILTER
DESIGN BY APPROXIMATION OF DERIVATIVES 703 10.3.2 IIR FILTER DESIGN BY
IMPULSE INVARIANCE 707 10.3.3 IIR FILTER DESIGN BY THE BILINEAR
TRANSFORMATION 712 10.3.4 CHARACTERISTICS OF COMMONLY USED ANALOG
FILTERS 717 10.3.5 SOME EXAMPLES OF DIGITAL FILTER DESIGNS BASED ON THE
BILINEAR 727 TRANSFORMATION 10.4 FREQUENCY TRANSFORMATIONS 730 10.4.1
FREQUENCY TRANSFORMATIONS IN THE ANALOG DOMAIN 730 10.4.2 FREQUENCY
TRANSFORMATIONS IN THE DIGITAL DOMAIN 732 10.5 SUMMARY AND REFERENCES
734 PROBLEMS 735 11 MULTIRATE DIGITAL SIGNAL PROCESSING 750 11.1
INTRODUCTION 751 11.2 DECIMATION BY A FACTOR D 755 11.3 INTERPOLATION BY
A FACTOR / 760 11.4 SAMPLING RATE CONVERSION BY A RATIONAL FACTOR I / D
762 11.5 IMPLEMENTATION OF SAMPLING RATE CONVERSION 766 11.5.1 POLYPHASE
FILTER STRUCTURES 766 11.5.2 INTERCHANGE OF FILTERS AND
DOWNSAMPLERS/UPSAMPLERS 767 11.5.3 SAMPLING RATE CONVERSION WITH
CASCADED INTEGRATOR COMB FILTERS 769 11.5.4 POLYPHASE STRUCTURES FOR
DECIMATION AND INTERPOLATION FILTERS 771 11.5.5 STRUCTURES FOR RATIONAL
SAMPLING RATE CONVERSION 774 CONTENTS XIII 11.6 MULTISTAGE
IMPLEMENTATION OF SAMPLING RATE CONVERSION 775 11.7 SAMPLING RATE
CONVERSION OF BANDPASS SIGNALS 779 11.8 SAMPLING RATE CONVERSION BY AN
ARBITRARY FACTOR 781 11.8.1 ARBITRARY RESAMPLING WITH POLYPHASE
INTERPOLATORS 782 11.8.2 ARBITRARY RESAMPLING WITH FARROW FILTER
STRUCTURES 782 11.9 APPLICATIONS OF MULTIRATE SIGNAL PROCESSING 784
11.9.1 DESIGN OF PHASE SHIFTERS 784 11.9.2 INTERFACING OF DIGITAL
SYSTEMS WITH DIFFERENT SAMPLING RATES 785 11.9.3 IMPLEMENTATION OF
NARROWBAND LOWPASS FILTERS 786 11.9.4 SUBBAND CODING OF SPEECH SIGNALS
787 11.10 DIGITAL FILTER BANKS 790 11.10.1 POLYPHASE STRUCTURES OF
UNIFORM FILTER BANKS 794 11.10.2 TRANSMULTIPLEXERS 796 11.11 TWO-CHANNEL
QUADRATURE MIRROR FILTER BANK 798 11.11.1 ELIMINATION OF ALIASING 799
11.11.2 CONDITION FOR PERFECT RECONSTRUCTION 801 11.11.3 POLYPHASE FORM
OF THE QMF BANK 801 11.11.4 LINEAR PHASE FIR QMF BANK 802 11.11.5 IIR
QMF BANK 803 11.11.6 PERFECT RECONSTRUCTION TWO-CHANNEL FIR QMF BANK 803
11.11.7 TWO-CHANNEL QMF BANKS IN SUBBAND CODING 806 11.12 M-CHANNEL QMF
BANK 807 11.12.1 ALIAS-FREE AND PERFECT RECONSTRUCTION CONDITION 808
11.12.2 POLYPHASE FORM OF THE M -CHANNEL QMF BANK 808 11.13 SUMMARY AND
REFERENCES 813 PROBLEMS 813 12 LINEAR PREDICTION AND OPTIMUM LINEAR
FILTERS 823 12.1 RANDOM SIGNALS, CORRELATION FUNCTIONS, AND POWER
SPECTRA 823 12.1.1 RANDOM PROCESSES 824 12.1.2 STATIONARY RANDOM
PROCESSES 825 12.1.3 STATISTICAL (ENSEMBLE) AVERAGES 825 12.1.4
STATISTICAL AVERAGES FOR JOINT RANDOM PROCESSES 826 12.1.5 POWER DENSITY
SPECTRUM 828 12.1.6 DISCRETE-TIME RANDOM SIGNALS 829 12.1.7 TIME
AVERAGES FOR A DISCRETE-TIME RANDOM PROCESS 830 12.1.8 MEAN-ERGODIC
PROCESS 831 12.1.9 CORRELATION-ERGODIC PROCESSES 832 XIV CONTENTS 12.2
INNOVATIONS REPRESENTATION OF A STATIONARY RANDOM PROCESS 834 12.2.1
RATIONAL POWER SPECTRA 836 12.2.2 RELATIONSHIPS BETWEEN THE FILTER
PARAMETERS AND THE 837 AUTOCORRELATION SEQUENCE 12.3 FORWARD AND
BACKWARD LINEAR PREDICTION 838 12.3.1 FORWARD LINEAR PREDICTION 839
12.3.2 BACKWARD LINEAR PREDICTION 841 12.3.3 * THE OPTIMUM REFLECTION
COEFFICIENTS FOR THE LATTICE FORWARD AND 845 * BACKWARD PREDICTORS
12.3.4 RELATIONSHIP OF AN AR PROCESS TO LINEAR PREDICTION 846 12.4
SOLUTION OF THE NORMAL EQUATIONS 846 12.4.1 THE LEVINSON-DURBIN
ALGORITHM 847 12.4.2 THE SCHUR ALGORITHM 850 12.5 PROPERTIES OF THE
LINEAR PREDICTION-ERROR FILTERS 855 12.6 AR LATTICE AND ARMA
LATTICE-LADDER FILTERS 858 12.6.1 AR LATTICE STRUCTURE 858 12.6.2 ARMA
PROCESSES AND LATTICE-LADDER FILTERS 860 12.7 WIENER FILTERS FOR
FILTERING AND PREDICTION 863 12.7.1 FIR WIENER FILTER 864 12.7.2
ORTHOGONALITY PRINCIPLE IN LINEAR MEAN-SQUARE ESTIMATION 866 12.7.3 IIR
WIENER FILTER 867 12.7.4 NONCAUSAL WIENER FILTER 872 12.8 SUMMARY AND
REFERENCES 873 PROBLEMS 874 13 ADAPTIVE FILTERS 880 13.1 APPLICATIONS OF
ADAPTIVE FILTERS 880 13.1.1 SYSTEM IDENTIFICATION OR SYSTEM MODELING 882
13.1.2 ADAPTIVE CHANNEL EQUALIZATION 883 13.1.3 ECHO CANCELLATION IN
DATA TRANSMISSION OVER TELEPHONE CHANNELS 887 13.1.4 SUPPRESSION OF
NARROWBAND INTERFERENCE IN A WIDEBAND SIGNAL 891 13.1.5 ADAPTIVE LINE
ENHANCER 895 13.1.6 ADAPTIVE NOISE CANCELLING 896 13.1.7 LINEAR
PREDICTIVE CODING OF SPEECH SIGNALS 897 13.1.8 ADAPTIVE ARRAYS 900 13.2
ADAPTIVE DIRECT-FORM FIR FILTERS*THE LMS ALGORITHM 902 13.2.1 MINIMUM
MEAN-SQUARE-ERROR CRITERION 903 13.2.2 THE LMS ALGORITHM 905 CONTENTS XV
13.2.3 RELATED STOCHASTIC GRADIENT ALGORITHMS 907 13.2.4 PROPERTIES OF
THE LMS ALGORITHM 909 13.3 ADAPTIVE DIRECT-FORM FILTERS*RLS ALGORITHMS
916 13.3.1 RLS ALGORITHM 916 13.3.2 THE LDU FACTORIZATION AND
SQUARE-ROOT ALGORITHMS 921 13.3.3 FAST RLS ALGORITHMS 923 13.3.4
PROPERTIES OF THE DIRECT-FORM RLS ALGORITHMS 925 13.4 ADAPTIVE
LATTICE-LADDER FILTERS 927 13.4.1 RECURSIVE LEAST-SQUARES LATTICE-LADDER
ALGORITHMS 928 13.4.2 OTHER LATTICE ALGORITHMS 949 13.4.3 PROPERTIES OF
LATTICE-LADDER ALGORITHMS 950 13.5 SUMMARY AND REFERENCES 954 PROBLEMS
955 14 POWER SPECTRUM ESTIMATION 960 14.1 ESTIMATION OF SPECTRA FROM
FINITE-DURATION OBSERVATIONS OF SIGNALS 961 14.1.1 COMPUTATION OF THE
ENERGY DENSITY SPECTRUM 961 14.1.2 ESTIMATION OF THE AUTOCORRELATION AND
POWER SPECTRUM OF RANDOM 966 SIGNALS: THE PERIODOGRAM 14.1.3 THE USE OF
THE DFT IN POWER SPECTRUM ESTIMATION 971 14.2 NONPARAMETRIC METHODS FOR
POWER SPECTRUM ESTIMATION 974 14.2.1 THE BARTLETT METHOD: AVERAGING
PERIODOGRAMS 974 14.2.2 THE WELCH METHOD: AVERAGING MODIFIED
PERIODOGRAMS 975 14.2.3 THE BLACKMAN AND TUKEY METHOD: SMOOTHING THE
PERIODOGRAM 978 14.2.4 PERFORMANCE CHARACTERISTICS OF NONPARAMETRIC
POWER SPECTRUM 981 ESTIMATORS 14.2.5 COMPUTATIONAL REQUIREMENTS OF
NONPARAMETRIC POWER SPECTRUM 984 ESTIMATES 14.3 PARAMETRIC METHODS FOR
POWER SPECTRUM ESTIMATION 986 14.3.1 RELATIONSHIPS BETWEEN THE
AUTOCORRELATION AND THE MODEL 988 PARAMETERS 14.3.2 THE YULE-WALKER
METHOD FOR THE AR MODEL PARAMETERS 990 14.3.3 THE BURG METHOD FOR THE AR
MODEL PARAMETERS 991 14.3.4 UNCONSTRAINED LEAST-SQUARES METHOD FOR THE
AR MODEL 994 PARAMETERS 14.3.5 SEQUENTIAL ESTIMATION METHODS FOR THE AR
MODEL PARAMETERS 995 14.3.6 SELECTION OF AR MODEL ORDER 996 14.3.7 MA
MODEL FOR POWER SPECTRUM ESTIMATION 997 14.3.8 ARMA MODEL FOR POWER
SPECTRUM ESTIMATION 999 14.3.9 SOME EXPERIMENTAL RESULTS 1001 XVI
CONTENTS 14.4 FILTER BANK METHODS 1009 14.4.1 FILTER BANK REALIZATION OF
THE PERIODOGRAM 1010 14.4.2 MINIMUM VARIANCE SPECTRAL ESTIMATES 1012
14.5 EIGENANALYSIS ALGORITHMS FOR SPECTRUM ESTIMATION 1015 14.5.1
PISARENKO HARMONIC DECOMPOSITION METHOD 1017 14.5.2 EIGEN-DECOMPOSITION
OF THE AUTOCORRELATION MATRIX FOR SINUSOIDS IN 1019 WHITE NOISE 14.5.3
|MUSIC ALGORITHM 1021 14.5.4 " ESPRIT ALGORITHM 1022 14.5.5 ORDER
SELECTION CRITERIA 1025 14.5.6 EXPERIMENTAL RESULTS 1026 14.6 SUMMARY
AND REFERENCES 1029 PROBLEMS 1030 A RANDOM NUMBER GENERATORS 1041 B
TABLES OF TRANSITION COEFFICIENTS FOR THE DESIGN OF LINEAR-PHASE 1047
FIR FILTERS REFERENCES AND BIBLIOGRAPHY 1053 ANSWERS TO SELECTED
PROBLEMS 1067 INDEX 1077 |
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| author | Proakis, John G. 1935- Manolakis, Dimitris G. |
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| dewey-full | 621.3822 |
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| dewey-sort | 3621.3822 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Elektrotechnik Elektrotechnik / Elektronik / Nachrichtentechnik |
| discipline_str_mv | Elektrotechnik Elektrotechnik / Elektronik / Nachrichtentechnik |
| edition | 4. ed. |
| format | Book |
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| id | DE-604.BV022232619 |
| illustrated | Illustrated |
| index_date | 2024-07-02T16:32:59Z |
| indexdate | 2024-07-09T20:52:57Z |
| institution | BVB |
| isbn | 0131873741 9780131873742 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015443676 |
| oclc_num | 255135078 |
| open_access_boolean | |
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| owner_facet | DE-573 DE-859 DE-861 DE-11 DE-739 DE-29T DE-91 DE-BY-TUM DE-Po75 |
| physical | XIX, 1084 S. Ill., graph. Darst. |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Prentice Hall |
| record_format | marc |
| spelling | Proakis, John G. 1935- Verfasser (DE-588)129254703 aut Digital signal processing [principles, algorithms, and applications] John G. Proakis ; Dimitris G. Manolakis 4. ed. Upper Saddle River, NJ Prentice Hall 2007 XIX, 1084 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing. Digitale Signalverarbeitung Digitale Signalverarbeitung (DE-588)4113314-6 gnd rswk-swf Digitale Signalverarbeitung (DE-588)4113314-6 s DE-604 Manolakis, Dimitris G. Verfasser (DE-588)1050810430 aut HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015443676&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Proakis, John G. 1935- Manolakis, Dimitris G. Digital signal processing [principles, algorithms, and applications] Digitale Signalverarbeitung Digitale Signalverarbeitung (DE-588)4113314-6 gnd |
| subject_GND | (DE-588)4113314-6 |
| title | Digital signal processing [principles, algorithms, and applications] |
| title_auth | Digital signal processing [principles, algorithms, and applications] |
| title_exact_search | Digital signal processing [principles, algorithms, and applications] |
| title_exact_search_txtP | Digital signal processing [principles, algorithms, and applications] |
| title_full | Digital signal processing [principles, algorithms, and applications] John G. Proakis ; Dimitris G. Manolakis |
| title_fullStr | Digital signal processing [principles, algorithms, and applications] John G. Proakis ; Dimitris G. Manolakis |
| title_full_unstemmed | Digital signal processing [principles, algorithms, and applications] John G. Proakis ; Dimitris G. Manolakis |
| title_short | Digital signal processing |
| title_sort | digital signal processing principles algorithms and applications |
| title_sub | [principles, algorithms, and applications] |
| topic | Digitale Signalverarbeitung Digitale Signalverarbeitung (DE-588)4113314-6 gnd |
| topic_facet | Digitale Signalverarbeitung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015443676&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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