Improved Exponential Stability Analysis for Delayed Recurrent Neural Networks
| Main Authors: | Miaomiao Yang, Shouming Zhong |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2014
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1090761 |
Daftar Isi:
- This paper studies the problem of exponential stability analysis for recurrent neural networks with time-varying delay.By establishing a suitable augmented LyapunovCKrasovskii function and a novel sufficient condition is obtained to guarantee the exponential stability of the considered system.In order to get a less conservative results of the condition,zero equalities and reciprocally convex approach are employed. The several exponential stability criterion proposed in this paper is simpler and effective. A numerical example is provided to demonstrate the feasibility and effectiveness of our results.