Adaptation in Dynamical Systems

Ivan Tyukin

doi:10.1017/CBO9780511973437

In the context of this book, adaptation is taken to mean a feature of a system aimed at achieving the best possible performance, when mathematical models of the environment and the system itself are not fully available. This has applications ranging from theories of visual perception and the processing of information, to the more technical problems of friction compensation and adaptive classification of signals in fixed-weight recurrent neural networks. Largely devoted to the problems of adaptive regulation, tracking and identification, this book presents a unifying system-theoretic view on the problem of adaptation in dynamical systems. Special attention is given to systems with nonlinearly parameterized models of uncertainty. Concepts, methods and algorithms given in the text can be successfully employed in wider areas of science and technology. The detailed examples and background information make this book suitable for a wide range of researchers and graduates in cybernetics, mathematical modelling and neuroscience.

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Contents

Frontmatter
pp i-iv
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Contents
pp v-viii
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Preface
pp ix-xiv
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Notational conventions
pp xv-xviii
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Part I - Introduction and preliminaries
pp 1-2
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1 - Introduction
pp 3-14
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2 - Preliminaries
pp 15-43
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3 - The problem of adaptation in dynamical systems
pp 44-80
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Part II - Theory
pp 81-82
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4 - Input–output analysis of uncertain dynamical systems
pp 83-150
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5 - Algorithms of adaptive regulation and adaptation in dynamical systems in the presence of nonlinear parametrization and/or possibly unstable target dynamics
pp 151-262
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Part III - Applications
pp 263-264
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6 - Adaptive behavior in recurrent neural networks with fixed weights
pp 265-293
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7 - Adaptive template matching in systems for processing of visual information
pp 294-349
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8 - State and parameter estimation of neural oscillators
pp 350-386
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Appendix. The Meyer–Kalman–Yakubovich lemma
pp 387-394
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References
pp 395-408
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Index
pp 409-410
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Adaptation in Dynamical Systems

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Contents

Frontmatter
pp i-iv

Contents
pp v-viii

Preface
pp ix-xiv

Notational conventions
pp xv-xviii

Part I - Introduction and preliminaries
pp 1-2

1 - Introduction
pp 3-14

2 - Preliminaries
pp 15-43

3 - The problem of adaptation in dynamical systems
pp 44-80

Part II - Theory
pp 81-82

4 - Input–output analysis of uncertain dynamical systems
pp 83-150

5 - Algorithms of adaptive regulation and adaptation in dynamical systems in the presence of nonlinear parametrization and/or possibly unstable target dynamics
pp 151-262

Part III - Applications
pp 263-264

6 - Adaptive behavior in recurrent neural networks with fixed weights
pp 265-293

7 - Adaptive template matching in systems for processing of visual information
pp 294-349

8 - State and parameter estimation of neural oscillators
pp 350-386

Appendix. The Meyer–Kalman–Yakubovich lemma
pp 387-394

References
pp 395-408

Index
pp 409-410

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Adaptation in Dynamical Systems

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