Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
411223 | Neurocomputing | 2007 | 7 Pages |
Abstract
This paper considers the problems of global exponential stability and exponential convergence rate for impulsive neural networks with time-varying delays and reaction–diffusion terms. By using Lyapunov functions method, some sufficient conditions ensuring global exponential stability of the networks are derived, and the estimated exponential convergence rate is also obtained. A numerical example is given at the end of this paper to demonstrate the effectiveness and applicability of the proposed criteria.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jianlong Qiu,