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Nederlands Buitenlands   Alles  Titel  Auteur  ISBN        
Technologie en beroepen
Energietechniek
Ogunfunmi, Tokunbo Adaptive Nonlinear System Identification
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Ogunfunmi, Tokunbo

Adaptive Nonlinear System Identification

The Volterra and Wiener Model Approaches

€ 151.75

Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identificatio


Taal / Language : English

Inhoudsopgave:
Preface vii
Acknowledgements xi
1 Introduction to Nonlinear Systems
1
1.1 Linear Systems
1
1.2 Nonlinear Systems
11
1.3 Summary
17
2 Polynomial Models of Nonlinear Systems
19
2.1 Nonlinear Orthogonal and Nonorthogonal Models
19
2.2 Nonorthogonal Models
20
2.3 Orthogonal Models
28
2.4 Summary
35
2.5 Appendix 2A (Sturm-Liouville System)
36
3 Volterra and Wiener Nonlinear Models
39
3.1 Volterra Respresentation
40
3.2 Discrete Nonlinear Wiener Representation
45
3.3 Detailed Nonlinear Wiener Model Representation
60
3.4 Delay Line Version of Nonlinear Wiener Model
65
3.5 The Nonlinear Hammerstein Model Representation
67
3.6 Summary
67
3.7 Appendix 3A
68
3.8 Appendix 3B
70
3.9 Appendix 3C
75
4 Nonlinear System Identification Methods
77
4.1 Methods Based on Nonlinear Local Optimization
77
4.2 Methods Based on Nonlinear Global Optimization
80
4.3 The Need for Adaptive Methods
81
4.4 Summary
84
5 Introduction to Adaptive Signal Processing
85
5.1 Weiner Filters for Optimum Linear Estimation
85
5.2 Adaptive Filters (LMS-Based Algorithms)
92
5.3 Applications of Adaptive Filters
95
5.4 Least-Squares Method for Optimum Linear Estimation
97
5.5 Adaptive Filters (RLS-Based Algorithms)
107
5.6 Summary
113
5.7 Appendix 5A
113
6 Nonlinear Adaptive System Identification Based on Volterra Models
115
6.1 LMS Algorithm for Truncated Volterra Series Model
116
6.2 LMS Algorithm for Bilinear Model of Nonlinear Systems
118
6.3 RLS Algorithm for Truncated Volterra Series Model
121
6.4 RLS Algorithm for Bilinear Model
122
6.5 Computer Simulation Examples
123
6.6 Summary
128
7 Nonlinear Adaptive System Identification Based on Wiener Models (Part 1)
129
7.1 Second-Order System
130
7.2 Computer Simulation Examples
140
7.3 Summary
148
7.4 Appendix 7A: Relation between Autocorrelation Matrix Rxx, Rxx, and Cross-Correlation Matrix Rxx
148
7.5 Appendix 7B: General Order Moments of Joint Gaussian Random Variables
150
8 Nonlinear Adaptive System Identification Based on Wiener Models (Part 2)
159
8.1 Third-Order System
159
8.2 Computer Simulation Examples
170
8.3 Summary
174
8.4 Appendix 8A: Relation Between Autocorrelation Matrix Rxx, Rxx, and Cross-Correlation Matrix Rxx
174
8.5 Appendix 8B: Inverse Matrix of Cross-Correlation Matrix Rxx
182
8.6 Appendix 8C: Verification of Equation 8.16
183
9 Nonlinear Adaptive System Identification Based on Wiener Models (Part 3)
187
9.1 Nonlinear LMF Adaptation Algorithm
187
9.2 Transform Domain Nonlinear Wiener Adaptive Filter
188
9.3 Computer Simulation Examples
193
9.4 Summary
197
10 Nonlinear Adaptive System Identification Based on Wiener Models (Part 4) 199
10.1 Standard RLS Nonlinear Wiener Adaptive Algorithm
200
10.2 Inverse QR Decomposition Nonlinear Wiener Filter Algorithm
201
10.3 Recursive OLS Volterra Adaptive Filtering
203
10.4 Computer Simulation Examples
208
10.5 Summary .
.212
11 Conclusions, Recent Results, and New Directions 213
11.1 Conclusions
214
11.2 Recent Results and New Directions
214
References 217
Index 225
Extra informatie: 
Hardback
248 pagina's
Januari 2007
537 gram
235 x 155 x 19 mm
Springer US us

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