Miaomiao Yang and Shouming Zhong
Improved Exponential Stability Analysis for Delayed Recurrent Neural Networks
153 - 159
2014
8
1
International Journal of Mathematical and Computational Sciences
https://publications.waset.org/pdf/9997445
https://publications.waset.org/vol/85
World Academy of Science, Engineering and Technology
This paper studies the problem of exponential stability analysis for recurrent neural networks with timevarying 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.
Open Science Index 85, 2014