| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 408385 | Neurocomputing | 2007 | 7 Pages |
Abstract
In this paper, a discrete-time bidirectional associative memory neural networks model is considered. By employing the theory of coincidence degree and using Halanay-type inequality technique we give some sufficient conditions ensuring the existence and globally exponential stability of periodic solutions for the discrete-time bidirectional neural networks. An example with the numerical simulations is provided to show the correctness of our analysis.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hongyong Zhao, Li Sun, Guanglan Wang,