Partial-Update Adaptive Signal Processing (eBook)

Design Analysis and Implementation

Kutluyil Dogancay (Autor)

eBook Download: EPUB

2008 | 1. Auflage
296 Seiten
Elsevier Science (Verlag)
978-0-08-092115-0 (ISBN)

Infos

Partial-update adaptive signal processing algorithms not only permit significant complexity reduction in adaptive filter implementations, but can also improve adaptive filter performance in telecommunications applications. This book gives state-of-the-art methods for the design and development of partial-update adaptive signal processing algorithms for use in systems development.
Partial-Update Adaptive Signal Processing provides a comprehensive coverage of key partial updating schemes, giving detailed information on the theory and applications of acoustic and network echo cancellation, channel equalization and multiuser detection. It also examines convergence and stability issues for partial update algorithms, providing detailed complexity analysis and a unifying treatment of partial-update techniques.
Features:
• Advanced analysis and design tools
• Application examples illustrating the use of partial-update adaptive signal processing
• MATLAB codes for developed algorithms
This unique reference will be of interest to signal processing and communications engineers, researchers, R&D engineers and graduate students.
'This is a very systematic and methodical treatment of an adaptive signal processing topic, of particular significance in power limited applications such as in wireless communication systems and smart ad hoc sensor networks. I am very happy to have this book on my shelf, not to gather dust, but to be consulted and used in my own research and teaching activities' - Professor A. G. Constantinides, Imperial College, London
About the author:
Kutluyil Dogançay is an associate professor of Electrical Engineering at the University of South Australia. His research interests span statistical and adaptive signal processing and he serves as a consultant to defence and private industry. He was the Signal Processing and Communications Program Chair of IDC Conference 2007, and is currently chair of the IEEE South Australia Communications and Signal Processing Chapter.
* Advanced analysis and design tools
* Algorithm summaries in tabular format
* Case studies illustrate the application of partial update adaptive signal processing
* MATLAB code listings on an accompanying website

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Partial-update adaptive signal processing algorithms not only permit significant complexity reduction in adaptive filter implementations, but can also improve adaptive filter performance in telecommunications applications. This book gives state-of-the-art methods for the design and development of partial-update adaptive signal processing algorithms for use in systems development.Partial-Update Adaptive Signal Processing provides a comprehensive coverage of key partial updating schemes, giving detailed information on the theory and applications of acoustic and network echo cancellation, channel equalization and multiuser detection. It also examines convergence and stability issues for partial update algorithms, providing detailed complexity analysis and a unifying treatment of partial-update techniques.Features:* Advanced analysis and design tools* Application examples illustrating the use of partial-update adaptive signal processing* MATLAB codes for developed algorithms This unique reference will be of interest to signal processing and communications engineers, researchers, R&D engineers and graduate students."e;This is a very systematic and methodical treatment of an adaptive signal processing topic, of particular significance in power limited applications such as in wireless communication systems and smart ad hoc sensor networks. I am very happy to have this book on my shelf, not to gather dust, but to be consulted and used in my own research and teaching activities"e; - Professor A. G. Constantinides, Imperial College, LondonAbout the author:Kutluyil Dogancay is an associate professor of Electrical Engineering at the University of South Australia. His research interests span statistical and adaptive signal processing and he serves as a consultant to defence and private industry. He was the Signal Processing and Communications Program Chair of IDC Conference 2007, and is currently chair of the IEEE South Australia Communications and Signal Processing Chapter. - Advanced analysis and design tools- Algorithm summaries in tabular format- Case studies illustrate the application of partial update adaptive signal processing

Inhalt

Front cover 1
Title page 2
Copyright page 3
Dedication 4
Acknowledgements 5
Table of Contents 6
Preface 12
Chapter 1. Introduction 14
Adaptive signal processing 14
Examples of adaptive filtering 14
Adaptive system identification 15
Adaptive inverse system identification 17
Raison d'être for partial coefficient updates 19
Resource constraints 19
Convergence performance 22
System identification with white input signal 23
System identification with correlated input signal 30
Chapter 2. Approaches to partial coefficient updates 38
Introduction 38
Periodic partial updates 39
Example 1: Convergence performance 43
Example 2: Convergence difficulties 44
Sequential partial updates 46
Example 1: Convergence performance 50
Example 2: Cyclostationary inputs 51
Example 3: Instability 52
Stochastic partial updates 56
System identification example 58
M -max updates 59
Example 1: Eigenvalue spread of RM 65
Example 2: Convergence performance 65
Example 3: Convergence rate and eigenvalues of RM 68
Example 4: Convergence difficulties 71
Example 5: Instability 72
Selective partial updates 73
Constrained optimization 74
Instantaneous approximation of Newton's method 78
q -Norm constrained optimization 80
Averaged system 83
Example 1: Eigenanalysis 83
Example 2: Convergence performance 84
Example 3: Instability 84
Set membership partial updates 87
Example 1: Convergence performance 91
Example 2: Instability 91
Block partial updates 91
Complexity considerations 95
Chapter 3. Convergence and stability analysis 96
Introduction 96
Convergence performance 96
Steady-state analysis 99
Partial-update LMS algorithms 100
Partial-update NLMS algorithms 105
Simulation examples for steady-state analysis 110
Convergence analysis 115
Partial-update LMS algorithms 121
Partial-update NLMS algorithms 138
Simulation examples for convergence analysis 144
Chapter 4. Partial-update adaptive filters 156
Introduction 156
Least-mean-square algorithm 157
Partial-update LMS algorithms 158
Periodic-partial-update LMS algorithm 158
Sequential-partial-update LMS algorithm 158
Stochastic-partial-update LMS algorithm 159
M -max LMS algorithm 160
Computational complexity 160
Normalized least-mean-square algorithm 162
Partial-update NLMS algorithms 164
Periodic-partial-update NLMS algorithm 164
Sequential-partial-update NLMS algorithm 164
Stochastic-partial-update NLMS algorithm 165
M -max NLMS algorithm 165
Selective-partial-update NLMS algorithm 165
Set-membership partial-update NLMS algorithm 166
Computational complexity 166
Affine projection algorithm 169
Partial-update affine projection algorithms 171
Periodic-partial-update APA 172
Sequential-partial-update APA 172
Stochastic-partial-update APA 173
M -max APA 173
Selective-partial-update APA 174
Set-membership partial-update APA 176
Selective-regressor APA 178
Computational complexity 180
Recursive least square algorithm 184
Partial-update RLS algorithms 189
Periodic-partial-update RLS algorithm 191
Sequential-partial-update RLS algorithm 192
Stochastic-partial-update RLS algorithm 192
Selective-partial-update RLS algorithm 192
Set-membership partial-update RLS algorithm 194
Partial-update RLS simulations 195
Computational complexity 196
Transform-domain least-mean-square algorithm 200
Power normalization 208
Comparison of power normalization algorithms 211
Partial-update transform-domain LMS algorithms 214
Periodic-partial-update transform-domain LMS algorithm 214
Sequential-partial-update transform-domain LMS algorithm 214
Stochastic-partial-update transform-domain LMS algorithm 214
M -max transform-domain LMS algorithm 215
Computational complexity 217
Generalized-subband-decomposition least-mean-square algorithm 220
Relationship between GSD-LMS coefficients and equivalent time-domain response 224
Eigenvalue spread of GSD input correlation matrix 226
Partial-update GSD-LMS algorithms 229
Periodic-partial-update GSD-LMS algorithm 229
Sequential-partial-update GSD-LMS algorithm 229
Stochastic-partial-update GSD-LMS algorithm 230
M -max GSD-LMS algorithm 231
Computational complexity 233
Simulation examples: Channel equalization 235
Chapter 5. Selected applications 246
Introduction 246
Acoustic echo cancellation 246
Network echo cancellation 249
PNLMS and -law PNLMS with selective partial updates 252
Blind channel equalization 258
Normalized CMA 262
Selective-partial-update NCMA 262
Simulation examples 264
Blind adaptive linear multiuser detection 266
MUD in synchronous DS-CDMA 269
Blind multiuser NLMS algorithm 272
Selective-partial-update NLMS for blind multiuser detection 273
Simulation examples 275
Chapter A. Overview of fast sorting algorithms 278
Introduction 278
Running min/max and sorting algorithms 278
Divide-and-conquer approaches 278
Maxline algorithm 281
The Gil--Werman algorithm 281
Sortline algorithm 282
Heapsort algorithm 283
References 285
Index 291

Produkt-Details

• Erscheint lt. Verlag: 17.9.2008
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Naturwissenschaften ► Physik / Astronomie ► Elektrodynamik
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Technik ► Nachrichtentechnik
• ISBN-10: 0-08-092115-9 / 0080921159
• ISBN-13: 978-0-08-092115-0 / 9780080921150