Partial-Update Adaptive Signal Processing: Design Analysis and Implementation > 신호처리

1 Introduction 1
1.1 Adaptive signal processing 1
1.2 Examples of adaptive filtering 1
1.3 Raison d'etre for partial coefficient updates 6
2 Approaches to partial coefficient updates 25
2.1 Introduction 25
2.2 Periodic partial updates 26
2.3 Sequential partial updates 33
2.4 Stochastic partial updates 43
2.5 M-max updates 47
2.6 Selective partial updates 61
2.7 Set membership partial updates 74
2.8 Block partial updates 78
2.9 Complexity considerations 82
3 Convergence and stability analysis 83
3.1 Introduction 83
3.2 Convergence performance 83
3.3 Steady-state analysis 86
3.4 Convergence analysis 102
4 Partial-update adaptive filters 143
4.1 Introduction 143
4.2 Least-mean-square algorithm 144
4.3 Partial-update LMS algorithms 145
4.4 Sequential least-mean-square algorithm 149
4.5 Partial-update NLMS algorithms 149
4.6 Affine projection algorithm 156
4.7 Partial-update affine projection algorithms 159
4.8 Recursive least square algorithm 171
4.9 Partial-update RLS algorithms 176
4.10 Transform-domain least-mean-square algorithm 187
4.11 Partial-update transform-domain LMS algorithms 201
4.12 Generalized-subband-decomposition least-mean-square algorithm 207
4.13 Partial-update GSD-LMS algorithms 216
4.14 Simulation examples: Channel equalization 222
5 Selected applications 233
5.1 Introduction 233
5.2 Acoustic echo cancellation 233
5.3 Network echo cancellation 236
5.4 Blind channel equalization 245
5.5 Blind adaptive linear multiuser detection 253
A Overview of fast sorting algorithms 265
A.1 Introduction 265
A.2 Running min/max and sorting algorithms 265
A.3 Heapsort algorithms 270
References273
Index 279