Fixed points and exponential stability for a stochastic neutral cellular neural network

Exponential stability for a stochastic delay neural network with impulses

*Correspondence: [email protected] 1School of Mathematical Science, Anhui University, Hefei, Anhui 230039, China 2Department of Mathematics and Physics, Anhui Jianzhu University, Hefei, Anhui 230601, China Abstract In this paper, we study the exponential stability for a stochastic neural network with impulses. By employing fixed point theory and some analysis techniques, sufficient conditions are ...

Monotonous stability for neutral fixed points

We give subtle, simple and precise results about the convergence or the divergence of the sequence (xn), where xj = f(xj−1) for every integer j, when the initial element x0 is in the neighbourhood of a neutral fixed point, i.e. a point x∗ such that f(x∗) = x∗ with |f ′(x∗)| = 1 (where f is a C∞ function defined on a subset of R).

Exponential stability analysis for delayed stochastic Cohen-Grossberg neural network

In this paper, the exponential stability problems are addressed for a class of delayed Cohen-Grossberg neural networks which are also perturbed by some stochastic noises. By employing the Lyapunov method, stochastic analysis and some inequality techniques, sufficient conditions are acquired for checking the pth(p > 1) and the 1st moment exponential stability of the network. Finally, One example...

Mean square exponential stability of stochastic delay cellular neural networks

The dynamical behaviors of stochastic neural networks have appeared as a novel subject of research and applications, such as optimization, control, and image processing(see [1-12]). Obviously, finding stability criteria for these neural networks becomes an attractive research problem of importance. Some well results have just appeared, for example, in [1-5], for stochastic delayed Hopfield neur...

Fixed Points and Stability in Neutral Stochastic Differential Equations with Variable Delays