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Exponential mean-square stability of stochastic string hybrid systems

2009 European Control Conference (ECC), 2009
The sufficient conditions of exponential mean-square stability for nonlinear continuous time stochastic string hybrid systems are established. The excitations are assumed to be parametric white noises and the switching rule has the form of a right continuous Markov chain. The detailed calculations are given for linear systems.
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The mean-square exponential stability and instability of stochastic nonholonomic systems

Chinese Physics, 2001
We present a new methodology for studying the mean-square exponential stability and instability of nonlinear nonholonomic systems under disturbance of Gaussian white-noise by the first approximation. Firstly, we give the linearized equations of nonlinear nonholonomic stochastic systems; then we construct a proper stochastic Lyapunov function to ...
Shang Mei, Guo Yong-xin
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Exponential Stability in Mean Square of Stochastic Functional Differential Equations with Infinite Delay

Acta Applicandae Mathematicae, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, Zhi, Xu, Liping
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Exponential stability in mean square for stochastic differential equations

Stochastic Analysis and Applications, 1990
In this paper we will consider the exponential stability in mean square for the following delay stochastic differential equation which might be regarded as a stochastic perturbed system of the equation The purpose of this paper is to prove that if Eq.(2) is exponentially stable, then Eq.(l) is also exponentially stable in mean square provided τ is ...
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New mean square exponential stability condition of stochastic fuzzy neural networks

Neurocomputing, 2015
This paper investigates the stability problem for interval type-2 (IT2) stochastic fuzzy neural networks. Firstly, an IT2 stochastic fuzzy neural network is constructed. Secondly, by using stochastic analysis approach and Ito?s differential formula, a new sufficient condition ensuring mean square exponential stability is obtained.
Xing Xing   +3 more
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Exponential mean square stability of stochastically forced 2-torus

Nonlinearity, 2004
Variety in the behaviour of nonlinear dynamic systems under transition from order to chaos is connected frequently with a chain of bifurcations: a stationary regime (equilibrium point) -- periodic regime (limit cycle) -- quasiperiodic regime (torus) -- chaotic regime (strange attractor). Each such transition is accompanied by the loss of stability of a
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New results on exponential stability in mean square of neutral stochastic equations with delays

International Journal of Control, 2021
This work addresses the exponential stability in mean square of general neutral stochastic differential equations with delays.
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EXPONENTIAL MEAN SQUARE STABILITY OF STOCHASTICALLY FORCED INVARIANT MANIFOLDS FOR NONLINEAR SDEs

Stochastics and Dynamics, 2007
An exponential mean square stability for the invariant manifold [Formula: see text] of a nonlinear stochastic system is considered. The stability analysis is based on the [Formula: see text]-quadratic Lyapunov function technique. The local dynamics of the nonlinear system near manifold is described by the stochastic linear extension system. We propose
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Preserving exponential mean-square stability in the simulation of hybrid stochastic differential equations

Numerische Mathematik, 2007
Some positive results are derived concerning the long time dynamics of fixed step size numerical simulations of stochastic differential equation systems with Markovian switching. It is shown that, under appropriate conditions, Euler-Maruyama and implicit theta-method discretisations can capture exponential mean-square stability for all sufficiently ...
Desmond J. Higham   +2 more
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New criteria for mean square exponential stability of stochastic delay differential equations

International Journal of Control, 2020
By a novel approach, we present several new criteria for the mean square exponential stability of general non-linear stochastic delay differential equations.
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