Adaptation in dynamical systems - Info and Reading Options
By Ivan Tyukin
"Adaptation in dynamical systems" was published by Cambridge University Press in 2011 - Cambridge, it has 410 pages and the language of the book is English.
“Adaptation in dynamical systems” Metadata:
- Title: ➤ Adaptation in dynamical systems
- Author: Ivan Tyukin
- Language: English
- Number of Pages: 410
- Publisher: Cambridge University Press
- Publish Date: 2011
- Publish Location: Cambridge
“Adaptation in dynamical systems” Subjects and Themes:
- Subjects: ➤ Control theory - Neurosciences - Mathematics - Mathematical models - Dynamics - SCIENCE / Physics - Adaptive control systems
Edition Specifications:
- Pagination: xvii, 410 pages :
Edition Identifiers:
- The Open Library ID: OL24881952M - OL15976862W
- Online Computer Library Center (OCLC) ID: 665137573
- Library of Congress Control Number (LCCN): 2010051427
- ISBN-13: 9780521198196
- All ISBNs: 9780521198196
AI-generated Review of “Adaptation in dynamical systems”:
"Adaptation in dynamical systems" Table Of Contents:
- 1- Machine generated contents note: Part I. Introduction and Preliminaries: 1. Introduction; 2. Preliminaries; 3. The problem of adaptation in dynamical systems; Part II. Theory: 4. Input-output analysis of uncertain dynamical systems; 5. Adaptive regulation in dynamical systems in presence of nonlinear parametrization and unstable target dynamics; Part III. Applications: 6. Adaptive behaviour in recurrent neural networks with fixed weights; 7. Adaptive template matching in systems for processing of visual information; 8. State and parameter estimation of neural oscillators; Appendix; References; Index.
"Adaptation in dynamical systems" Description:
The Open Library:
"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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