In this paper, the problems of exponential stability analysis and stabilization are investigated for sampled-data systems with probabilistic sampling. By introducing a stochastic variable satisfying a Bernoulli distribution, the probabilistic sampling system is transformed into a continuous time-delay system with stochastic parameters. A Lyapunov functional approach is developed to establish th...

1School of Business Administration, Southwestern University of Finance and Economics No. 555, Liutai Ave, Wenjiang Zone, Chengdu 611130, China 2Yangtze Normal University, No. 98, Julong Ave, Fuling Zone, Chongqing, 408100, China 3School of Management and Economics University of Electronic Science and Technology of China No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China e-mail: koug...

The stability of the signed regressor variant of least mean square (LMS) adaptation is found to be heavily dependent on the characteristics of the input sequence. Averaging theory is used to derive a persistence of excitation condition which guarantees exponential stability of the signed regressor algorithm. Failure to meet this condition (which is not equivalent to persistent excitation for LM...

Stochastic effects on convergence dynamics of reaction-diffusion Cohen-Grossberg neural networks CGNNs with delays are studied. By utilizing Poincaré inequality, constructing suitable Lyapunov functionals, and employing the method of stochastic analysis and nonnegative semimartingale convergence theorem, some sufficient conditions ensuring almost sure exponential stability and mean square expon...

This paper studies the asymptotic behavior for a class of delayed reaction-diffusion Hopfield neural networks driven by finite-dimensional Wiener processes. Some new sufficient conditions are established to guarantee the mean square exponential stability of this system by using Poincaré’s inequality and stochastic analysis technique. The proof of the almost surely exponential stability for this...

In this paper, we study the stability of quasilinear parabolic stochastic partial differential equations with multiplicative noise, which are neither monotone nor locally monotone. The exponential mean square and pathwise solutions established. Moreover, under certain hypothesis on perturbations, can be derived, without utilizing stability.

In this paper, a class of hybrid impulsive systems with time delays and stochastic effects are considered. We obtain some criteria on the global exponential stability in mean square for the impulsive stochastic delayed systems. To do this, differential inequalities and L-operator inequalities are developed. An example is given to illustrate the effectiveness of our results.

This paper deals with robust exponential stability of Markovian jumping stochastic Cohen–Grossberg neural networks (MJSCGNNs) with mode-dependent probabilistic time-varying delays, continuously distributed delays and impulsive perturbations. By construction of novel Lyapunov–Krasovskii functional having the triple integral terms, the double integral terms having the positive definite matrices d...