2005
DOI: 10.1016/j.jde.2005.05.008
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Stability of nonautonomous differential equations in Hilbert spaces

Abstract: We introduce a large class of nonautonomous linear differential equations v =A(t)v in Hilbert spaces, for which the asymptotic stability of the zero solution, with all Lyapunov exponents of the linear equation negative, persists in v =A(t)v +f (t, v) under sufficiently small perturbations f. This class of equations, which we call Lyapunov regular, is introduced here inspired in the classical regularity theory of Lyapunov developed for finite-dimensional spaces, that is nowadays apparently overlooked in the the… Show more

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Cited by 25 publications
(31 citation statements)
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“…We note that Theorem 12 is a discrete time version of results in [2]. The following is another stability result.…”
Section: Stability For Nonuniform Contractionsmentioning
confidence: 78%
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“…We note that Theorem 12 is a discrete time version of results in [2]. The following is another stability result.…”
Section: Stability For Nonuniform Contractionsmentioning
confidence: 78%
“…where C(n, 1) is defined in a similar manner to that in (2). Therefore, C(n, 1)e i , e j = U * n A(n, 1)e i , e j = A(n, 1)e i , U n e j = v i (n), u j (n) = 0 whenever i < j, in view of (27).…”
Section: Upper Triangular Reductionmentioning
confidence: 99%
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“…We emphasize that in a certain sense our assumptions are the weakest possible under which it is possible to establish the persistence of the stability. We refer to [3] for a detailed related discussion in the case of ordinary differential equations. We also refer to the book [9] for a detailed discussion of the geometric theory in the infinite-dimensional setting, with emphasis on delay differential equations.…”
Section: Introductionmentioning
confidence: 99%
“…Essentially, the existence of nonzero Lyapunov exponents leads to a nonuniform exponential behavior. We refer to the books [1,3] for detailed discussions. Here we consider only the case of negative Lyapunov exponents, and of delay r = 0 in equation (1.5), with Y = R p for some p ∈ N. In this case, each linear operator L m is a p × p matrix A m , and if lim sup…”
Section: Introductionmentioning
confidence: 99%