Exponential Stability of Stochastic Neural Networks with Mixed Time-Delays

摘要

This paper investigates the exponential stability of stochastic neural networks with unbounded discrete delays and infinitely distributed delays. By using Lyapunov functions, the semi-martingale convergence theorem and some inequality techniques, the exponential stability in mean square and almost sure exponential stability are obtained. To overcome the difficulties from unbounded delays, some new techniques are introduced. Some earlier results are improved and generalized. An example is given to illustrate the results.