Adaptive Signal Processing

Applications to Real-World Problems

By: Jacob Benesty (Editor), Yiteng Huang (Editor)

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Hardcover | 6 February 2003

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Hardcover
376 Pages

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24.13 x 17.15 x 3.18

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The goal of this book is to provide, for the first time, a reference to the most relevant applications of adaptive filtering techniques. Top researchers in the field contributed chapters addressing their specific topic of study. The topics are limited to those applications in acoustics, speech, wireless, and networking where research is still very active and open. The book is roughly organized into two parts. In the first part, several applications in acoustics and speech are developed. The second part focuses on wireless and networking applications. Some chapters are tutorial in nature, while others present new research ideas, and all have in common the use of adaptive algorithms to solve real-world problems.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Digital Signal Processing (DSP)Engineering & Technology Electronics & Communications Engineering Communications Engineering & Telecommunications Energy Technology & Engineering Electrical Engineering Computer Networking & Communications Mechanical Engineering & Materials Mechanical Engineering

Other Technologies & Applied Sciences Applied Optics Imaging Systems & Technology Electronics Engineering Microwave Technology Computer Hardware Network Hardware

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Paperback

Published: 5th December 2010

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On a Class of Exponentiated Adaptive Algorithms for the Identification of Sparse Impulse Responses	p. 1
Introduction	p. 1
Derivation of the Different Algorithms	p. 2
Link Between the LMS and EG Algorithms and Normalized Versions	p. 5
The RLS and ERLS Algorithms	p. 9
Link Between the PNLMS and EG[plus and minus] Algorithms	p. 10
Application of the EG[plus and minus] Algorithm for Blind Channel Identification	p. 12
Simulations	p. 15
Conclusions	p. 20
References	p. 21
Adaptive Feedback Cancellation in Hearing Aids	p. 23
Introduction	p. 23
Steady-State Analysis	p. 26
The Feedback Path	p. 29
Real-World Processing Concerns	p. 30
Feedback Cancellation System	p. 32
Initialization	p. 32
Running Adaptation	p. 35
Performance Metric	p. 36
Constrained Adaptation	p. 37
Adaptation with Clamp	p. 37
Adaptation with Cost Function	p. 40
Simulation Results	p. 41
Filtered-X System	p. 44
Room Reverberation Effects	p. 47
Test Configuration	p. 47
Initialization and Measurement Procedure	p. 49
Measured Feedback Path	p. 49
Maximum Stable Gain	p. 52
Conclusions	p. 53
References	p. 55
Single-Channel Acoustic Echo Cancellation	p. 59
Introduction	p. 59
Settings	p. 61
Loudspeaker-Enclosure-Microphone Systems	p. 61
Electronic Replica of LEM Systems	p. 63
Speech Signals	p. 65
Background Noise	p. 67
Regulations	p. 68
Methods for Acoustic Echo Control	p. 69
Loss Control	p. 70
Echo Cancellation	p. 70
Echo Suppression	p. 71
Adaptive Algorithms	p. 72
NLMS Algorithm	p. 73
AP Algorithm	p. 74
RLS Algorithm	p. 76
Adaptation Control	p. 77
Optimal Step Size for the NLMS Algorithm	p. 78
A Method for Estimating the Optimal Step Size	p. 80
Suppression of Residual Echoes	p. 82
Processing Structures	p. 87
Fullband Processing	p. 87
Block Processing	p. 88
Subband Processing	p. 88
Conclusions	p. 89
References	p. 91
Multichannel Frequency-Domain Adaptive Filtering with Application to Multichannel Acoustic Echo Cancellation	p. 95
Introduction	p. 95
General Derivation of Multichannel Frequency-Domain Algorithms	p. 98
Optimization Criterion	p. 98
Normal Equation	p. 102
Adaptation Algorithm	p. 103
Convergence Analysis	p. 105
Analysis Model	p. 106
Convergence in Mean	p. 107
Convergence in Mean Square	p. 107
Generalized Frequency-Domain Adaptive MIMO Filtering	p. 110
Approximation and Special Cases	p. 112
Approximation of the Frequency-Domain Kalman Gain	p. 113
Special Cases	p. 114
A Dynamical Regularization Strategy	p. 116
Efficient Multichannel Realization	p. 117
Efficient Calculation of the Frequency-Domain Kalman Gain	p. 117
Dynamical Regularization for Proposed Kalman Gain Approach	p. 119
Efficient DFT Calculation of Overlapping Data Blocks	p. 120
Simulations and Real-World Applications	p. 122
Multichannel Acoustic Echo Cancellation	p. 123
Adaptive MIMO Filtering for Hands-Free Speech Communication	p. 125
Conclusions	p. 126
References	p. 127
Filtering Techniques for Noise Reduction and Speech Enhancement	p. 129
Introduction	p. 129
Noise Reduction with an Array	p. 131
Adaptive Noise Cancellation	p. 137
Spectral Modification with a Single Microphone	p. 144
Parametric Spectral Subtraction	p. 145
Estimation of the Noise Spectrum	p. 146
Parametric Wiener Filtering	p. 148
Estimation of the Wiener Gain Filter	p. 150
Conclusions	p. 151
References	p. 153
Adaptive Beamforming for Audio Signal Acquisition	p. 155
Introduction	p. 155
Signal Model, Sensor Arrays, and Concepts	p. 157
Sensor Array, Sensor Signals, and Beamformer Setup	p. 157
Interference-Independent Beamformer Performance Measures	p. 159
Interference-Dependent Beamformer Performance Measures	p. 161
Data-Independent Beamformer Design	p. 162
Optimum Data-Dependent Beamformer Designs	p. 165
Least-Squares Error (LSE) Design	p. 166
Least-Squares Formulation of Linearly Constrained Minimum Variance (LCMV) Beamforming: LCMV-LS Design	p. 169
Eigenvector Beamformers	p. 175
Suppression of Correlated Interference	p. 177
Adaptation of LCMV-LS Beamformers	p. 178
A Practical Audio Acquisition System Using a Robust GSC	p. 180
Spatio-Temporal Constraints	p. 181
Robust GSC After [1] as an LCMV-LS Beamformer with Spatio-Temporal Constraints	p. 182
Realization in the DFT-Domain	p. 185
Experimental Evaluation	p. 186
Conclusions	p. 187
References	p. 188
Blind Source Separation of Convolutive Mixtures of Speech	p. 195
Introduction	p. 195
What Is BSS?	p. 196
Mixed Signal Model for Speech Signals in a Room	p. 197
Unmixed Signal Model	p. 197
Task of Blind Source Separation of Speech Signals	p. 198
Instantaneous Mixtures vs. Convolutive Mixtures	p. 198
Time-Domain Approach vs. Frequency-Domain Approach	p. 199
Time-Domain Approach for Convolutive Mixtures	p. 199
Frequency-Domain Approach for Convolutive Mixtures	p. 200
Scaling and Permutation Problems	p. 200
What Is ICA?	p. 201
What Is Independence?	p. 201
Minimization of Mutual Information	p. 202
Maximization of Nongaussianity	p. 202
Maximization of Likelihood	p. 202
Three ICA Theories Are Identical	p. 203
Learning Rules	p. 204
How Speech Signals Can Be Separated?	p. 204
Second Order Statistics vs. Higher Order Statistics	p. 205
Second Order Statistics (SOS) Approach	p. 206
Higher Order Statistics (HOS) Approach	p. 207
Physical Interpretation of BSS	p. 207
Frequency-Domain Adaptive Beamformer (ABF)	p. 208
ABF for Target S[subscript 1] and Jammer S[subscript 2]	p. 208
ABF for Target S[subscript 2] and Jammer S[subscript 1]	p. 210
Two Sets of ABFs	p. 210
Equivalence Between BSS and Adaptive Beamformers	p. 210
When S[subscript 1] [not equal] 0 and S[subscript 2] [not equal] 0	p. 211
When S[subscript 1] [not equal] 0 and S[subscript 2] = 0	p. 212
When S[subscript 1] = 0 and S[subscript 2] [not equal] 0	p. 213
Separation Mechanism of BSS	p. 213
Fundamental Limitation of BSS	p. 214
When Sources Are Near the Microphones	p. 214
When Sources Are Not "Independent"	p. 215
BSS Is Upper Bounded by ABF	p. 216
BSS Is an Intelligent Version of ABF	p. 216
Sound Quality	p. 217
Directivity Patterns of NBF, BSS, and ABF	p. 219
Experimental Conditions	p. 220
Mixing Systems	p. 220
Source Signals	p. 220
Evaluation Measure	p. 221
Scaling and Permutation	p. 222
Conclusions	p. 222
References	p. 223
Adaptive Multichannel Time Delay Estimation Based on Blind System Identification for Acoustic Source Localization	p. 227
Introduction	p. 227
Problem Formulation	p. 229
Notation	p. 229
Signal Model	p. 230
Channel Properties and Assumptions	p. 231
Generalized Multichannel Time Delay Estimation	p. 232
The Principle	p. 232
Time-Domain Multichannel LMS Approach	p. 233
Frequency-Domain Adaptive Algorithms	p. 234
Algorithm Implementation	p. 237
Simulations	p. 238
Experimental Setup	p. 238
Performance Measure	p. 242
Experimental Results	p. 242
Conclusions	p. 243
References	p. 246
Algorithms for Adaptive Equalization in Wireless Applications	p. 249
Introduction	p. 249
Criteria for Equalization	p. 251
Channel Equalization	p. 253
Infinite Filter Length Solutions for Single Channels	p. 254
Finite and Infinite Filter Length Solutions for Multiple Channels	p. 255
Finite Filter Length Solutions for Single Channels	p. 258
Decision Feedback Equalizers	p. 261
Adaptive Algorithms for Channel Equalization	p. 265
Adaptively Minimizing ZF	p. 265
Adaptively Minimizing MMSE	p. 267
Training and Tracking	p. 267
Channel Estimation	p. 269
Channel Estimation in MIMO Systems	p. 270
Estimation of Wireless Channels	p. 271
Channel Estimation by Basis Functions	p. 271
Channel Estimation by Predictive Methods	p. 272
Maximum Likelihood Equalization	p. 273
Viterbi Algorithm	p. 274
Blind Algorithms	p. 275
Conclusions	p. 277
References	p. 277
Adaptive Space-Time Processing for Wireless CDMA	p. 283
Introduction	p. 283
Data Model	p. 285
The Blind 2D RAKE Receiver	p. 287
The Blind 2D STAR	p. 288
Decision-Feedback Identification (DFI)	p. 288
Parallel and Soft DFI	p. 289
Parallel and Hard DFI	p. 291
Common and Soft DFI	p. 293
Common and Hard DFI	p. 295
Performance Gains of the DFI Versions	p. 300
The Blind 1D-ST STAR	p. 301
1D-ST Structured Data Model	p. 302
2D STAR with Common DFI Reinterpreted	p. 302
1D-ST Structured DFI	p. 303
Performance Gains of 1D-ST STAR over 2D STAR	p. 305
The Pilot-Assisted 1D-ST STAR	p. 311
Data Model with Pilot Signals	p. 311
1D-ST STAR with Conventional Pilot-Channel Use	p. 313
1D-ST STAR with Enhanced Pilot-Channel Use	p. 314
1D-ST STAR with Conventional Pilot-Symbol Use	p. 315
1D-ST STAR with Enhanced Pilot-Symbol Use	p. 316
Performance Gains with Enhanced Pilot Use	p. 316
Conclusions	p. 318
References	p. 319
The IEEE 802.11 System with Multiple Receive Antennas	p. 323
Introduction	p. 323
System Model with Multiple Receive Antennas	p. 326
Estimating the Receive Antenna Weights	p. 328
The IEEE 802.11 Distributed Coordination Function with Multiple Packet Reception	p. 328
Throughput Analysis	p. 330
All Successful Packets Acknowledged	p. 332
Only a Single Successful Packet Acknowledged	p. 334
Performance Results	p. 335
Conclusions	p. 338
References	p. 339
Adaptive Estimation of Clock Skew and Different Types of Delay in the Internet Network	p. 341
Introduction	p. 341
Terminology and Problem Formulation	p. 342
Delay Jitter Model	p. 344
The Least-Squares (LS) Estimator	p. 344
The Maximum Likelihood (ML) Estimator and Linear Programming	p. 346
An Unbiased RLS Algorithm	p. 347
Simulations	p. 348
Conclusions	p. 349
References	p. 351
Index	p. 353
Table of Contents provided by Ingram. All Rights Reserved.

Adaptive Signal Processing

Applications to Real-World Problems

At a Glance

Hardcover

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How to return your order

Defective items

You Can Find This Book In

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