Abstract
In this paper, we consider the problem on exponential stability analysis of the stochastic impulsive high-order BAM neural networks with time delays. Through employing Lyapunov function method and stochastic bidirected halanay inequality, we constitute exponential stability of the stochastic impulsive high-order BAM neural networks with its estimated exponential convergence rate and feasible interval of impulsive strength. An example illustrates the main results. © 2012 Springer-Verlag London Limited.
| Original language | English |
|---|---|
| Pages (from-to) | 1-8 |
| Journal | Neural Computing and Applications |
| Volume | 23 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jul 2013 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to <a href="mailto:[email protected]">[email protected]</a>.Research Keywords
- Exponential stability
- Impulsive effects
- Stochastic high-order BAM neural networks
- Time-varying delays
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