| Description |
1 online resource (xvii, 410 pages) : illustrations |
| Physical Medium |
polychrome |
| Description |
text file |
| Summary |
"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"-- Provided by publisher. |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Cover -- Half-title -- Title -- Copyright -- Contents -- Preface -- Notational conventions -- Part I Introduction and preliminaries -- 1 Introduction -- 1.1 Observation problems -- 1.2 Regulation problems -- 1.3 Summary -- 2 Preliminaries -- 2.1 Attracting sets and attractors -- 2.2 Barbalat's lemma -- 2.3 Basic notions of stability -- 2.4 The method of Lyapunov functions -- 2.5 Linear skew-symmetric systems with time-varying coefficients -- 3 The problem of adaptation in dynamical systems -- 3.1 Logical principles of adaptation -- 3.2 Formal definitions of adaptation and mathematical statements of the problem of adaptation -- 3.3 Adaptive control for nonlinear deterministic dynamical systems -- 3.4 Applicability issues of conventional methods of adaptive control and regulation -- 3.5 Summary -- Part II Theory -- 4 Input -- output analysis of uncertain dynamical systems -- 4.1 Operator description of dynamical systems -- 4.2 Inputoutput and inputstate characterizations of stable systems -- 4.3 Inputoutput and inputstate analysis of uncertain unstable systems -- 4.4 Asymptotic properties of systems withlocally bounded inputoutput and inputstate mappings -- 4.5 Asymptotic properties of a class of unstable systems -- Appendix to Chapter 4 -- 5 Algorithms of adaptive regulation and adaptation in dynamical systems in the presence of nonlinear parametrization and/or possibly unstable target dynamics -- 5.1 Problems of adaptive control of nonlinear systems in the presence of nonlinear parametrization -- 5.2 Direct adaptive control -- 5.3 Adaptive regulation to invariant sets -- 5.4 Adaptive control of interconnected dynamical systems -- 5.5 Non-dominating adaptive control for dynamical systems with nonlinear parametrization of a general kind -- 5.6 Parametric identification of dynamical systems with nonlinear parametrization -- Appendix to Chapter 5 -- Part III Applications -- 6 Adaptive behavior in recurrent neural networks with fixed weights -- 6.1 Signals to be classified -- 6.2 The class of recurrent neural networks -- 6.3 Assumptions and statement of the problem -- 6.4 The existence result -- 6.5 Summary -- 7 Adaptive template matching in systems for processing of visual information -- 7.1 Preliminaries and problem formulation -- 7.2 A simple adaptive system for invariant template matching -- 7.3 Examples -- 7.4 Summary -- 8 State and parameter estimation of neural oscillators -- 8.1 Observer-based approaches to the problem of stateand parameter estimation -- 8.2 The feasibility of conventional adaptive-observer canonical forms -- 8.3 Universal adaptive observers for conductance-based models -- 8.4 Examples -- 8.5 Summary -- Appendix. The MeyerKalmanYakubovich lemma -- References -- Index. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Dynamics.
|
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Dynamics. |
|
Control theory -- Mathematical models.
|
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Control theory -- Mathematical models. |
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Neurosciences -- Mathematics.
|
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Neurosciences -- Mathematics. |
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Neurosciences. |
| Genre/Form |
Electronic books.
|
| Other Form: |
Print version: Tyukin, Ivan. ADAPTATION IN DYNAMICAL SYSTEMS. Cambridge : Cambridge University Press, 2011, ©2011 9780521198196 (DLC) 2010051427 (OCoLC)665137573 |
| ISBN |
9780511860874 (electronic book) |
|
0511860870 (electronic book) |
|
9780511973437 (electronic book) |
|
0511973438 (electronic book) |
|
9780521198196 |
|
0521198194 |
| Standard No. |
9786613006042 |
|
