Adaptive Filtering: algorithms and practical implementation
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer
2008
|
| Ausgabe: | 3. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XXIV, 627 S. graph. Darst. |
| ISBN: | 9780387312743 9780387686066 0387312749 |
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Datensatz im Suchindex
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| adam_text | PAULO S.R. DINIZ ADAPTIVE FILTERING ALGORITHMS AND PRACTICAL
IMPLEMENTATION THIRD EDITION SPRINGER CONTENTS PREFACE X 1 INTRODUCTION
TO ADAPTIVE FILTERING 1 1.1 INTRODUCTION 1 2 4 7 11 13 13 14 14 15 21 23
34 39 43 44 47 48 49 54 54 55 56 57 65 67 68 70 1.2 1.3 1.4 1.5 ADAPTIVE
SIGNAL PROCESSING INTRODUCTION TO ADAPTIVE ALGORITHMS APPLICATIONS
REFERENCES FUNDAMENTALS OF ADAPTIVE FILTERING 2.1 2.2 2.3 2.4 2.5 2.6
2.7 2.8 2.9 2.10 2.11 2.12 2.13 INTRODUCTION SIGNAL REPRESENTATION 2.2.1
DETERMINISTIC SIGNALS 2.2.2 RANDOM SIGNALS 2.2.3 ERGODICITY THE
CORRELATION MATRIX WIENER FILTER LINEARLY CONSTRAINED WIENER FILTER
2.5.1 THE GENERALIZED SIDELOBE CANCELLER MEAN-SQUARE ERROR SURFACE BIAS
AND CONSISTENCY NEWTON ALGORITHM STEEPEST-DESCENT ALGORITHM APPLICATIONS
REVISITED 2.10.1 SYSTEM IDENTIFICATION 2.10.2 SIGNAL ENHANCEMENT 2.10.3
SIGNAL PREDICTION 2.10.4 CHANNEL EQUALIZATION 2.10.5 DIGITAL
COMMUNICATION SYSTEM CONCLUDING REMARKS REFERENCES PROBLEMS XVIII
CONTENTS THE LEAST-MEAN-SQUARE (LMS) ALGORITHM 77 3.1 INTRODUCTION 77
3.2 THE LMS ALGORITHM 77 3.3 SOME PROPERTIES OF THE LMS ALGORITHM 79
3.3.1 GRADIENT BEHAVIOR - . 79 3.3.2 CONVERGENCE BEHAVIOR OF THE
COEFFICIENT VECTOR 80 3.3.3 COEFFICIENT-ERROR-VECTOR COVARIANCE MATRIX
82 3.3.4 BEHAVIOR OF THE ERROR SIGNAL 85 3.3.5 MINIMUM MEAN-SQUARE ERROR
85 3.3.6 EXCESS MEAN-SQUARE ERROR AND MISADJUSTMENT 87 3.3.7 TRANSIENT
BEHAVIOR 89 3.4 LMS ALGORITHM BEHAVIOR IN NONSTATIONARY ENVIRONMENTS 90
3.5 COMPLEX LMS ALGORITHM 94 3.6 EXAMPLES 95 3.6.1 ANALYTICAL EXAMPLES
95 3.6.2 SYSTEM IDENTIFICATION SIMULATIONS 107 3.6.3 CHANNEL
EQUALIZATION SIMULATIONS 113 3.6.4 FAST ADAPTATION SIMULATIONS 114 3.6.5
THE LINEARLY CONSTRAINED LMS ALGORITHM 118 3.7 CONCLUDING REMARKS 121
3.8 REFERENCES 124 3.9 PROBLEMS 126 LMS-BASED ALGORITHMS 131 4.1
INTRODUCTION 131 4.2 QUANTIZED-ERROR ALGORITHMS 132 4.2.1 SIGN-ERROR
ALGORITHM 133 4.2.2 DUAL-SIGN ALGORITHM 140 4.2.3 POWER-OF-TWO ERROR
ALGORITHM 141 4.2.4 SIGN-DATA ALGORITHM 141 4.3 THE LMS-NEWTON ALGORITHM
143 4.4 THE NORMALIZED LMS ALGORITHM 145 4.5 THE TRANSFORM-DOMAIN LMS
ALGORITHM 147 4.6 THE AFFINE PROJECTION ALGORITHM 156, 4.6.1
MISADJUSTMENT IN THE AFFINE PROJECTION ALGORITHM 161 4.6.2 BEHAVIOR IN
NONSTATIONARY ENVIRONMENTS 169 4.6.3 TRANSIENT BEHAVIOR 171 4.6.4
COMPLEX AFFINE PROJECTION ALGORITHM 173 CONTENTS XIX 4.7 SIMULATION
EXAMPLES 174 4.7.1 SIGNAL ENHANCEMENT SIMULATION 178 4.7.2 SIGNAL
PREDICTION SIMULATION 180 4.8 CONCLUDING REMARKS 183 4.9 REFERENCES 186
4.10 PROBLEMS 189 CONVENTIONAL RLS ADAPTIVE FILTER 195 5.1 INTRODUCTION
195 5.2 THE RECURSIVE LEAST-SQUARES ALGORITHM 195 5.3 PROPERTIES OF THE
LEAST-SQUARES SOLUTION 200 5.3.1 ORTHOGONALITY PRINCIPLE 200 5.3.2
RELATION BETWEEN LEAST-SQUARES AND WIENER SOLUTIONS 201 5.3.3 INFLUENCE
OF THE DETERMINISTIC AUTOCORRELATION INITIALIZATION 203 5.3.4
STEADY-STATE BEHAVIOR OF THE COEFFICIENT VECTOR 203 5.3.5
COEFFICIENT-ERROR-VECTOR COVARIANCE MATRIX 205 5.3.6 BEHAVIOR OF THE
ERROR SIGNAL 207 5.3.7 EXCESS MEAN-SQUARE ERROR AND MISADJUSTMENT 210
5.4 BEHAVIOR IN NONSTATIONARY ENVIRONMENTS 215 5.5 COMPLEX RLS ALGORITHM
219 5.6 SIMULATION EXAMPLES 221 5.7 CONCLUDING REMARKS ~ 223 5.8
REFERENCES 227 5.9 PROBLEMS 227 DATA-SELECTIVE ADAPTIVE FILTERING 231
6.1 INTRODUCTION . 231 6.2 SET-MEMBERSHIP FILTERING 232 6.3
SET-MEMBERSHIP NORMALIZED LMS ALGORITHM 234 6.4 SET-MEMBERSHIP AFFINE
PROJECTION ALGORITHM 237 6.4.1 A TRIVIAL CHOICE FOR VECTOR 7(FC) 241
6.4.2 A SIMPLE VECTOR 7 (FC) 242 6.4.3 REDUCING THE COMPLEXITY IN THE
SIMPLIFIED SM-AP ALGORITHM 243 6.5 SET-MEMBERSHIP BINORMALIZED LMS
ALGORITHMS 245 6.5.1 SM-BNLMS ALGORITHM 1 247 6.5.2 SM-BNLMS ALGORITHM 2
249 6.6 COMPUTATIONAL COMPLEXITY 251 6.7 TIME-VARYING 7 252 6.8
PARTIAL-UPDATE ADAPTIVE FILTERING 254 6.8.1 SET-MEMBERSHIP
PARTIAL-UPDATE NLMS ALGORITHM 256 XX CONTENTS 6.9 SIMULATION EXAMPLES
260 6.9.1 ECHO CANCELLATION ENVIRONMENT 264 6.9.2 WIRELESS CHANNEL
ENVIRONMENT 271 6.10 CONCLUDING REMARKS 280 6.11 REFERENCES 281 6.12
PROBLEMS 283 7 ADAPTIVE LATTICE-BASED RLS ALGORITHMS 289 7.1
INTRODUCTION 289 7.2 RECURSIVE LEAST-SQUARES PREDICTION - 290 7.2.1
FORWARD PREDICTION PROBLEM 290 7.2.2 BACKWARD PREDICTION PROBLEM 293 7.3
ORDER-UPDATING EQUATIONS 295 7.3.1 A NEW PARAMETER 6(K, I) 295 7.3.2
ORDER UPDATING OF JF M . N (FC, I) AND W B (FC, I) 29 7 7.3.3 ORDER
UPDATING OF ^ MIN (K, I) AND W/ (K, I) 298 7.3.4 ORDER UPDATING OF
PREDICTION ERRORS 298 7.4 TIME-UPDATING EQUATIONS 300 7.4.1 TIME
UPDATING FOR PREDICTION COEFFICIENTS 300 7.4.2 TIME UPDATING FOR 5(K, I)
302 7.4.3 ORDER UPDATING FOR J(K, I) 304 7.5 JOINT-PROCESS ESTIMATION
307 7.6 TIME RECURSIONS OF THE LEAST-SQUARES ERROR 311 7.7 NORMALIZED
LATTICE RLS ALGORITHM 313 7.7.1 BASIC ORDER RECURSIONS 313 7.7.2
FEEDFORWARD FILTERING 315 7.8 ERROR-FEEDBACK LATTICE RLS ALGORITHM 318
7.8.1 RECURSIVE FORMULAS FOR THE REFLECTION COEFFICIENTS 318 7.9 LATTICE
RLS ALGORITHM BASED ON A PRIORI ERRORS 319 7.10 QUANTIZATION EFFECTS 321
7.11 CONCLUDING REMARKS 327 7.12 REFERENCES 328 7.13 PROBLEMS 329 8 FAST
TRANSVERSAL RLS ALGORITHMS 333 8.1 INTRODUCTION 333 8.2 RECURSIVE
LEAST-SQUARES PREDICTION 334 8.2.1 FORWARD PREDICTION RELATIONS 334
8.2.2 BACKWARD PREDICTION RELATIONS 335 8.3 JOINT-PROCESS ESTIMATION 337
CONTENTS XXI 8.4 STABILIZED FAST TRANSVERSAL RLS ALGORITHM 339 8.5
CONCLUDING REMARKS 345 8.6 REFERENCES 346 8.7 PROBLEMS 347 9
QR-DECOMPOSITION-BASED RLS FILTERS 351 9.1 INTRODUCTION 351 9.2
TRIANGULARIZATION USING QR-DECOMPOSITION 351 9.2.1 INITIALIZATION
PROCESS 353 9.2.2 INPUT DATA MATRIX TRIANGULARIZATION 353 9.2.3
QR-DECOMPOSITION RLS ALGORITHM 360 9.3 SYSTOLIC ARRAY IMPLEMENTATION 365
9.4 SOME IMPLEMENTATION ISSUES 372 9.5 FAST QR-RLS ALGORITHM 373 9.5.1
BACKWARD PREDICTION PROBLEM 376 9.5.2 FORWARD PREDICTION PROBLEM 378 9.6
CONCLUSIONS AND FURTHER READING 384 9.7 REFERENCES 387 9.8 PROBLEMS 389
10 ADAPTIVE IIR FILTERS 395 10.1 INTRODUCTION 395 10.2 OUTPUT-ERROR IIR
FILTERS 396 10.3 GENERAL DERIVATIVE IMPLEMENTATION 400 10.4 ADAPTIVE
ALGORITHMS 402 10.4.1 RECURSIVE LEAST-SQUARES ALGORITHM 402 10.4.2 THE
GAUSS-NEWTON ALGORITHM 404 10.4.3 GRADIENT-BASED ALGORITHM 407 10.5
ALTERNATIVE ADAPTIVE FILTER STRUCTURES 407 10.5.1 CASCADE FORM 407
10.5.2 LATTICE STRUCTURE 409 10.5.3 PARALLEL FORM 416 10.5.4
FREQUENCY-DOMAIN PARALLEL STRUCTURE 417 10.6 MEAN-SQUARE ERROR SURFACE
426 10.7 INFLUENCE OF THE FILTER STRUCTURE ON THE MSE SURFACE 433 10.8
ALTERNATIVE ERROR FORMULATIONS 435 10.8.1 EQUATION ERROR FORMULATION 435
10.8.2 THE STEIGLITZ-MCBRIDE METHOD 439 10.9 CONCLUSION 442
LO.LOREFERENCES 443 10.11 PROBLEMS 446 XXII CONTENTS 11 NONLINEAR
ADAPTIVE FILTERING 451 11.1 INTRODUCTION 451 11.2 THE VOLTERRA SERIES
ALGORITHM 452 11.2.1 LMS VOLTERRA FILTER 454 11.2.2 RLS VOLTERRA FILTER
457 11.3 ADAPTIVE BILINEAR FILTERS 464 11.4 MULTILAYER PERCEPTRON
ALGORITHM 469 11.5 RADIAL BASIS FUNCTION ALGORITHM 473 11.6 CONCLUSION
480 11.7 REFERENCES 482 11.8 PROBLEMS 484 12 SUBBAND ADAPTIVE FILTERS
485 12.1 INTRODUCTION 485 12.2 MULTIRATE SYSTEMS 486 12.2.1 DECIMATION
AND INTERPOLATION 486 12.3 FILTER BANKS 488 12.3.1 TWO-BAND PERFECT
RECONSTRUCTION FILTER BANKS 493 12.3.2 ANALYSIS OF TWO-BAND FILTER BANKS
494 12.3.3 ANALYSIS OF M-BAND FILTER BANKS 494 12.3.4 HIERARCHICAL
M-BAND FILTER BANKS 495 12.3.5 COSINE-MODULATED FILTER BANKS 495 12.3.6
BLOCK REPRESENTATION 497 12.4 SUBBAND ADAPTIVE FILTERS 497 12.4.1
SUBBAND IDENTIFICATION 501 12.4.2 TWO-BAND IDENTIFICATION 502 12.4.3
CLOSED-LOOP STRUCTURE 502 12.5 CROSS-FILTERS ELIMINATION 508 12.5.1
FRACTIONAL DELAYS * 510 12.6 DELAYLESS SUBBAND ADAPTIVE FILTERING 515
12.6.1 COMPUTATIONAL COMPLEXITY 517 12.7 FREQUENCY-DOMAIN ADAPTIVE
FILTERING 521 12.8 CONCLUSION 530 12.9 REFERENCES 531 12.10PROBLEMS 533
13 BLIND ADAPTIVE FILTERING 537 13.1 INTRODUCTION 537 CONTENTS XXIII
13.2 CONSTANT-MODULUS ALGORITHM 538 13.2.1 GODARD ALGORITHM 539 13.2.2
CONSTANT-MODULUS ALGORITHM 540 13.2.3 SATO ALGORITHM 540 13.2.4 ERROR
SURFACE OF CMA 542 13.3 AFFINE PROJECTION CM ALGORITHM 549 13.4 BLIND
SIMO EQUALIZERS 555 13.4.1 IDENTIFICATION CONDITIONS 557 13.5 SIMO-CMA
EQUALIZER 558 13.6 CONCLUDING REMARKS 564 13.7 REFERENCES 565 13.8
PROBLEMS 567 A COMPLEX DIFFERENTIATION 571 A.I INTRODUCTION 571 A.2 THE
COMPLEX WIENER SOLUTION 571 A.3 DERIVATION OF THE COMPLEX LMS ALGORITHM
574 A.4 USEFUL RESULTS 575 B QUANTIZATION EFFECTS IN THE LMS ALGORITHM
577 B.I INTRODUCTION 577 B.2 ERROR DESCRIPTION 577 B.3 ERROR MODELS FOR
FIXED-POINT ARITHMETIC 579 B.4 COEFFICIENT- ERROR- VECTOR COVARIANCE
MATRIX 580 B.5 ALGORITHM STOP 582 B.6 MEAN-SQUARE ERROR 582 B.7
FLOATING-POINT ARITHMETIC IMPLEMENTATION 584 B.8 FLOATING-POINT
QUANTIZATION ERRORS IN LMS ALGORITHM 585 C QUANTIZATION EFFECTS IN THE
RLS ALGORITHM 589 C.I INTRODUCTION 589 C.2 ERROR DESCRIPTION 589 C.3
ERROR MODELS FOR FIXED-POINT ARITHMETIC 591 C.4 COEFFICIENT-ERROR-VECTOR
COVARIANCE MATRIX 592 C.5 ALGORITHM STOP 595 C.6 MEAN-SQUARE ERROR 596
C.7 FIXED-POINT IMPLEMENTATION ISSUES 597 C.8 FLOATING-POINT ARITHMETIC
IMPLEMENTATION 597 C.9 FLOATING-POINT QUANTIZATION ERRORS IN RLS
ALGORITHM 600 XXIV CONTENTS D KALMAN FILTERS 605 D.I INTRODUCTION 605
D.2 STATE-SPACE MODEL 605 D.2.1 SIMPLE EXAMPLE 606 D.3 KALMAN FILTERING
608 D.4 KALMAN FILTER AND RLS 614 D.5 REFERENCES 615 INDEX 617
|
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| discipline | Mathematik Elektrotechnik / Elektronik / Nachrichtentechnik |
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| publisher | Springer |
| record_format | marc |
| spelling | Diniz, Paulo Sergio Ramirez Verfasser aut Adaptive Filtering algorithms and practical implementation Paulo S. R. Diniz 3. ed. New York, NY Springer 2008 XXIV, 627 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Algorithmes Filtres adaptatifs Traitement adaptatif du signal Traitement du signal - Méthodes statistiques Adaptive filters Adaptive signal processing Algorithms Signal processing Statistical methods Digitale Signalverarbeitung (DE-588)4113314-6 gnd rswk-swf Adaptives Filter (DE-588)4141377-5 gnd rswk-swf Digitale Signalverarbeitung (DE-588)4113314-6 s Adaptives Filter (DE-588)4141377-5 s DE-604 text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2809012&prov=M&dok_var=1&dok_ext=htm Inhaltstext HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017357090&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Diniz, Paulo Sergio Ramirez Adaptive Filtering algorithms and practical implementation Algorithmes Filtres adaptatifs Traitement adaptatif du signal Traitement du signal - Méthodes statistiques Adaptive filters Adaptive signal processing Algorithms Signal processing Statistical methods Digitale Signalverarbeitung (DE-588)4113314-6 gnd Adaptives Filter (DE-588)4141377-5 gnd |
| subject_GND | (DE-588)4113314-6 (DE-588)4141377-5 |
| title | Adaptive Filtering algorithms and practical implementation |
| title_auth | Adaptive Filtering algorithms and practical implementation |
| title_exact_search | Adaptive Filtering algorithms and practical implementation |
| title_full | Adaptive Filtering algorithms and practical implementation Paulo S. R. Diniz |
| title_fullStr | Adaptive Filtering algorithms and practical implementation Paulo S. R. Diniz |
| title_full_unstemmed | Adaptive Filtering algorithms and practical implementation Paulo S. R. Diniz |
| title_short | Adaptive Filtering |
| title_sort | adaptive filtering algorithms and practical implementation |
| title_sub | algorithms and practical implementation |
| topic | Algorithmes Filtres adaptatifs Traitement adaptatif du signal Traitement du signal - Méthodes statistiques Adaptive filters Adaptive signal processing Algorithms Signal processing Statistical methods Digitale Signalverarbeitung (DE-588)4113314-6 gnd Adaptives Filter (DE-588)4141377-5 gnd |
| topic_facet | Algorithmes Filtres adaptatifs Traitement adaptatif du signal Traitement du signal - Méthodes statistiques Adaptive filters Adaptive signal processing Algorithms Signal processing Statistical methods Digitale Signalverarbeitung Adaptives Filter |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=2809012&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017357090&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT dinizpaulosergioramirez adaptivefilteringalgorithmsandpracticalimplementation |