Ultimate Boundedness of Stochastic Hopfield Neural Networks
Li Wan, Qinghua Zhou · Journal of Convergence Information Technology · 2011
Abstract Hopfield neural networks with nonlinear and delay-type template elements have been extensively studied in past years and found many applications for solving a number of problems in various scientific disciplines. Although ultimate boundedness of several classes of neural networks with constant delays was studied by some researchers, the inherent randomness associated with signal transmission was not taken account into these networks. So far there are not any results on ultimate boundedness of stochastic neural networks with delays. This paper investigates ultimate boundedness of stochastic Hopfield neural networks with delays and establishs some sufficient criteria on stochasitc ultimate boundedness by employing Lyapunov method. One example is given to demonstrate our criteria.