This paper is concerned with the stability of impulsive stochastic reaction-diffusion differential systems with mixed time delays. First, an equivalent relation between the solution of a stochastic reaction-diffusion differential system with time delays and impulsive effects and that of corresponding system without impulses is established. Then, some stability criteria for the stochastic reaction-diffusion differential system with time delays and impulsive effects are derived. Finally, the stability criteria are applied to impulsive stochastic reaction-diffusion Cohen-Grossberg neural networks with mixed time delays, and sufficient conditions are obtained for the exponential p-stability of the zero solution to the neural networks. An exampl...
AbstractThis work concerns the stability for impulsive delayed Cohen-Grossberg neural networks with ...
This article studies the practical exponential stability of impulsive stochastic reaction-diffusion ...
This work is devoted to investigating the stability of impulsive cellular neural networks with time-...
This paper studies the stability of hybrid impulsive and switching stochastic neural networks. First...
The main purpose of this paper is to further investigate the stability problem of impulsive neural n...
In this paper, the problem of stability analysis for a class of impulsive Cohen-Grossberg neural net...
This paper is concerned with pth moment exponential stability of stochastic reaction-diffusion Cohen...
The main aim of this paper is to discuss moment exponential stability for a stochastic reaction-diff...
This work concerns the stability of impulsive Cohen-Grossberg neural networks with time-varying dela...
In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy neural ne...
This paper concerns the problem of exponential stability for a class of Cohen-Grossberg neural netwo...
AbstractIn this paper, the dynamic behaviors of a class of stochastic neural networks with time-vary...
We study the exponential stability of the complex dynamical network described by differentially nonl...
AbstractThe problem of stability analysis of stochastic BAM neural networks with time delays and imp...
The problem of global exponential stability analysis of impulsive neural networks with variable dela...
AbstractThis work concerns the stability for impulsive delayed Cohen-Grossberg neural networks with ...
This article studies the practical exponential stability of impulsive stochastic reaction-diffusion ...
This work is devoted to investigating the stability of impulsive cellular neural networks with time-...
This paper studies the stability of hybrid impulsive and switching stochastic neural networks. First...
The main purpose of this paper is to further investigate the stability problem of impulsive neural n...
In this paper, the problem of stability analysis for a class of impulsive Cohen-Grossberg neural net...
This paper is concerned with pth moment exponential stability of stochastic reaction-diffusion Cohen...
The main aim of this paper is to discuss moment exponential stability for a stochastic reaction-diff...
This work concerns the stability of impulsive Cohen-Grossberg neural networks with time-varying dela...
In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy neural ne...
This paper concerns the problem of exponential stability for a class of Cohen-Grossberg neural netwo...
AbstractIn this paper, the dynamic behaviors of a class of stochastic neural networks with time-vary...
We study the exponential stability of the complex dynamical network described by differentially nonl...
AbstractThe problem of stability analysis of stochastic BAM neural networks with time delays and imp...
The problem of global exponential stability analysis of impulsive neural networks with variable dela...
AbstractThis work concerns the stability for impulsive delayed Cohen-Grossberg neural networks with ...
This article studies the practical exponential stability of impulsive stochastic reaction-diffusion ...
This work is devoted to investigating the stability of impulsive cellular neural networks with time-...