Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
469808 | Computers & Mathematics with Applications | 2008 | 6 Pages |
Abstract
The stability of a class of stochastic Recurrent Neural Networks with time-varying delays is investigated in this paper. With the help of the Lyapunov function and the Dini derivative of the expectation of V(t,X(t))V(t,X(t)) “along” the solution X(t)X(t) of the model, a set of novel sufficient conditions on mean square exponential stability has been established. An example is also given to illustrate the effectiveness of our results.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Chuangxia Huang, Yigang He, Hainu Wang,