Stochastic Stability of Cohen-grossberg Neural Networks with Unbounded Distributed Delays
نویسندگان
چکیده
In this article, we consider a model that describes the dynamics of Cohen-Grossberg neural networks with unbounded distributed delays, whose state variable are governed by stochastic non-linear integro-differential equations. Without assuming the smoothness, monotonicity and boundedness of the activation functions, by constructing suitable Lyapunov functional, employing the semi-martingale convergence theorem and some inequality, we obtain some sufficient criteria to check the almost exponential stability of networks.
منابع مشابه
Robust stability of fuzzy Markov type Cohen-Grossberg neural networks by delay decomposition approach
In this paper, we investigate the delay-dependent robust stability of fuzzy Cohen-Grossberg neural networks with Markovian jumping parameter and mixed time varying delays by delay decomposition method. A new Lyapunov-Krasovskii functional (LKF) is constructed by nonuniformly dividing discrete delay interval into multiple subinterval, and choosing proper functionals with different weighting matr...
متن کاملStability analysis for stochastic Cohen-Grossberg neural network with distributed delays and reaction diffusion terms
This paper mainly deals with the almost surely exponential stability and exponential p-th moment stability for a class of stochastic Cohen–Grossberg neural networks with distributed delays and reaction–diffusion term. By constructing suitable Lyapunov functional, employing the nonnegative semi-martingale convergence theorem and applying matrix theory and stochastic analysis technique, two delay...
متن کاملStability Analysis of Impulsive Stochastic Cohen-Grossberg Neural Networks with Mixed Time Delays
In this paper, the problem of stability analysis for a class of impulsive stochastic Cohen-Grossberg neural networks with mixed delays is considered. The mixed time delays comprise both the time-varying and infinite distributed delays. By employing a combination of the M -matrix theory and stochastic analysis technique, a sufficient condition is obtained to ensure the existence, uniqueness, and...
متن کاملAnalysis of stability for impulsive stochastic fuzzy Cohen-Grossberg neural networks with mixed delays
In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy Cohen-Grossberg neural networks with mixed delays is considered. Based on M-matrix theory and stochastic analysis technique, a sufficient condition is obtained to ensure the existence, uniqueness, and global exponential stability in mean square means of the equilibrium point for the addressed impulsive st...
متن کاملGlobal stability of Cohen-Grossberg neural network with both time-varying and continuous distributed delays
In this paper, a generalized neural network of Cohen-Grossberg type with both discrete time-varying and distributed unbounded delays is considered. Based on M-matrix theory, sufficient conditions are established to ensure the existence and global attractivity of an equilibrium point. The global exponential stability of the equilibrium is also addressed but for the model with bounded discrete ti...
متن کامل