Results 21 to 30 of about 2,662,596 (297)
Advances in Difference Equations, 2020 This paper is concerned with the asymptotic stability of linear fractional-order neutral delay differential–algebraic systems described by the Caputo–Fabrizio (CF) fractional derivative.
Ann Al Sawoor
doaj +1 more source
THE EXTENT OF ASYMPTOTIC STABILITY [PDF]
Proceedings of the National Academy of Sciences, 1960 Voranzeige [vgl. IRE Trans. Circuit Theory CT-7, 520--527 (1960)]. Es handelt sich um Bedingungen vom Typ der Ljapunovschen Stabilitätssätze dafür, daß die Trajektorien eines Differentialgleichungssystems gegen eine gewisse Punktmenge \( M \) streben. Wenn \( M \) der Ursprung ist, hat man den Ljapunovschen Fall.
openaire +3 more sources
Advances in Difference Equations, 2021 The problem of asymptotic stability and extended dissipativity analysis for the generalized neural networks with interval discrete and distributed time-varying delays is investigated.
Sunisa Luemsai +2 more
doaj +1 more source
A note on asymptotic stability [PDF]
Proceedings of the American Mathematical Society, 1968 where x is an m-vector, A and B(t) are complex m Xm matrices, A is constant and skew-Hermitian (A* = -A), B is continuous for all real t and of period w> 0, and e is a small positive number. The problem of deciding the asymptotic behavior of the solutions of such a system is a common one in perturbation theory.
openaire +2 more sources
Stability in asymptotically AdS spaces [PDF]
Journal of High Energy Physics, 2005 We discuss two types of instabilities which may arise in string theory compactified to asymptotically AdS spaces: perturbative, due to discrete modes in the spectrum of the Laplacian, and non-perturbative, due to brane nucleation. In the case of three dimensional Einstein manifolds, we completely characterize the presence of these instabilities, and in
Kleban, Matthew +2 more
openaire +3 more sources
Asymptotic Stability in Reservoir Computing
2022 International Joint Conference on Neural Networks (IJCNN), 2022 Reservoir Computing is a class of Recurrent Neural Networks with internal weights fixed at random. Stability relates to the sensitivity of the network state to perturbations. It is an important property in Reservoir Computing as it directly impacts performance.
Dong, Jonathan +3 more
openaire +3 more sources
Asymptotic Stability and Asymptotic Synchronization of Memristive Regulatory-Type Networks
Advances in Mathematical Physics, 2017 Memristive regulatory-type networks are recently emerging as a potential successor to traditional complementary resistive switch models. Qualitative analysis is useful in designing and synthesizing memristive regulatory-type networks.
Jin-E Zhang
doaj +1 more source
Polynomial asymptotic stability of damped stochastic differential equations. [PDF]
, 2004 The paper studies the polynomial convergence of solutions of a scalar nonlinear Itˆo stochastic differential equation dX(t) = −f(X(t)) dt + (t) dB(t) where it is known, a priori, that limt!1 X(t) = 0, a.s. The intensity of the stochastic perturbation
Appleby, John A.D., Mackey, Dana
core +3 more sources
Exponential stability for a class of set dynamic equations on time scales
Journal of Inequalities and Applications, 2022 We first present a new definition for some form of exponential stability of solutions, including H-exponential stability, H-exponentially asymptotic stability, H-uniformly exponential stability, and H-uniformly exponentially asymptotic stability for a ...
Keke Jia +3 more
doaj +1 more source
On Stability of Linear Delay Differential Equations under Perron's Condition
Abstract and Applied Analysis, 2011 The stability of the zero solution of a system of first-order linear functional differential equations with nonconstant delay is considered. Sufficient conditions for stability, uniform stability, asymptotic stability, and uniform asymptotic stability ...
J. Diblík, A. Zafer
doaj +1 more source