New PDF release: Adaptation in Dynamical Systems

By Ivan Tyukin

ISBN-10: 0521198194

ISBN-13: 9780521198196

Within the context of this booklet, edition is taken to intend a function of a approach aimed toward reaching the absolute best functionality, while mathematical versions of our environment and the approach itself usually are not totally to be had. This has purposes starting from theories of visible conception and the processing of data, to the extra technical difficulties of friction reimbursement and adaptive class of indications in fixed-weight recurrent neural networks. principally dedicated to the issues of adaptive rules, monitoring and identity, this e-book provides a unifying system-theoretic view at the challenge of model in dynamical structures. precise realization is given to platforms with nonlinearly parameterized versions of uncertainty. suggestions, equipment and algorithms given within the textual content might be effectively hired in wider components of technology and know-how. The distinct examples and heritage info make this ebook compatible for quite a lot of researchers and graduates in cybernetics, mathematical modelling and neuroscience.

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Extra resources for Adaptation in Dynamical Systems

Example text

1 and lim x(t, x0 ) − x(t, x0 ) = 0. 3(a). In order to tell whether x(t, x0 ) is stable we have to compare the values of x(t, x0 ) and x(t, x0 ) at the same values of t. Clearly, Lyapunov stability does not exhaust the whole spectrum of plausible asymptotic descriptions of solutions of a dynamical system with respect to each other. Consider an example. Let x(t, x0 ) and x(t, x0 ) be two solutions of the same system, and x0 = x0 . Then a possible characterization of their relative position in the state space could be ρ(t, x(t, x0 ), x(t, x0 )) = x(t, x0 ) A A = {p ∈ Rn |p = x(t, x0 ), t ∈ R}.

2 This led to the emergence of the new notion of a weakly attracting set, which was formally defined by J. 4 A set A is a weakly attracting, or Milnor attracting, set iff (1) it is closed, invariant, and (2) for some set V (not necessarily a neighborhood of A) with strictly positive measure and for all x0 ∈ V the following limiting relation holds: lim x(t, x0 ) = A ∀ x0 ∈ V (A). 3 is that the domain of attraction V is not necessarily a neighborhood of A. Despite the fact that this difference may look small and insignificant at first glance, it becomes very instrumental for successful statement and solution of particular problems of adaptation.

3). This figure demonstrates that for any neighborhood U (A) of the origin A there are points x ∈ U (A) such that solutions x(t, x ) escape the neighborhood U (A) and never come back. 3, A cannot be called an attracting set. On the other hand, there are points x ∈ U (A) such that limt→∞ x(t, x ) = 0. If U (A) is an open circle, then the number of such points is as large as the number of points corresponding to the solutions escaping U (A). Thus the set A bears an overall signature of attractivity.

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Adaptation in Dynamical Systems by Ivan Tyukin


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