Dynamic System Identification: Experiment Design and Data Analysis

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Author(s): Graham C. Goodwin and Robert L. Payne (Eds.)
Series: Mathematics in Science and Engineering 136
Edition: 1st
Publisher: Academic Press
Year: 1977

Language: English
Pages: iii-x, 1-291

Content:
Edited by
Page iii

Copyright page
Page iv

Preface
Pages ix-x

Chapter 1 Introduction and Statistical Background
Pages 1-21

Chapter 2 Linear Least Squares and Normal Theory
Pages 22-44

Chapter 3 Maximum Likelihood Estimators
Pages 45-60

Chapter 4 Models for Dynamic Systems
Pages 61-81

Chapter 5 Estimation for Dynamic Systems
Pages 82-123

Chapter 6 Experiment Design
Pages 124-174

Chapter 7 Recursive Algorithms
Pages 175-208

Appendix A Summary of Results from Distribution Theory
Pages 209-219

Appendix B Limit Theorems
Pages 220-224

Appendix C Stochastic Processes
Pages 225-233

Appendix D Martingale Convergence Results
Pages 234-240

Appendix E Mathematical Results
Pages 241-245

Problem Solutions
Pages 246-275

References
Pages 276-286

Index
Pages 287-291