By using the concept of differential equations with piecewise constant argument of generalized type, a model of stochastic cellular neural networks with piecewise constant argument is developed. Sufficient conditions are obtained for the existence and uniqueness of the equilibrium point for the addressed neural networks. pth moment exponential stability is investigated by means of Lyapunov functional, stochastic analysis, and inequality technique. The results in this paper improve and generalize some of the previous ones. An example with numerical simulations is given to illustrate our results
In this article we study a cellular neural network with impulsive effects. By using differential in...
AbstractBy using M-matrix theory, some inequality analysis technology and mathematical induction, so...
AbstractIn this paper, the existence and uniqueness of the equilibrium point and absolute stability ...
AbstractIn this paper, by using the concept of differential equations with piecewise constant argume...
We introduce impulsive cellular neural network models with piecewise alternately advanced and retard...
By using the semi-discretization technique of differential equations, the discrete analogue of a kin...
AbstractIn this paper, the problem of global exponential stability for cellular neural networks (CNN...
In this study, we develop a model of recurrent neural networks with functional dependence on piecewi...
This work addresses the stability study for stochastic cellular neural networks with time-varying de...
This paper presents new sufficient conditions for the global exponential stability of the equilibriu...
A new criterion on exponential stability of the equilibrium point for a class of discrete cellular n...
The main aim of this paper is to discuss moment exponential stability for a stochastic reaction-diff...
The stability of stochastic delayed Cellular Neural Networks (DCNN) is investigated in this paper. U...
The stability analysis of neural networks is important in the applications and has been studied by m...
We consider a new model for shunting inhibitory cellular neural networks, retarded functional differ...
In this article we study a cellular neural network with impulsive effects. By using differential in...
AbstractBy using M-matrix theory, some inequality analysis technology and mathematical induction, so...
AbstractIn this paper, the existence and uniqueness of the equilibrium point and absolute stability ...
AbstractIn this paper, by using the concept of differential equations with piecewise constant argume...
We introduce impulsive cellular neural network models with piecewise alternately advanced and retard...
By using the semi-discretization technique of differential equations, the discrete analogue of a kin...
AbstractIn this paper, the problem of global exponential stability for cellular neural networks (CNN...
In this study, we develop a model of recurrent neural networks with functional dependence on piecewi...
This work addresses the stability study for stochastic cellular neural networks with time-varying de...
This paper presents new sufficient conditions for the global exponential stability of the equilibriu...
A new criterion on exponential stability of the equilibrium point for a class of discrete cellular n...
The main aim of this paper is to discuss moment exponential stability for a stochastic reaction-diff...
The stability of stochastic delayed Cellular Neural Networks (DCNN) is investigated in this paper. U...
The stability analysis of neural networks is important in the applications and has been studied by m...
We consider a new model for shunting inhibitory cellular neural networks, retarded functional differ...
In this article we study a cellular neural network with impulsive effects. By using differential in...
AbstractBy using M-matrix theory, some inequality analysis technology and mathematical induction, so...
AbstractIn this paper, the existence and uniqueness of the equilibrium point and absolute stability ...