Abstract
In this paper, we study a class of stochastic neutral cellular neural networks. By constructing a suitable Lyapunov functional and employing the nonnegative semi-martingale convergence theorem we give some sufficient conditions ensuring the almost sure exponential stability of the networks. The results obtained are helpful to design stability of networks when stochastic noise is taken into consideration. Finally, two examples are provided to show the correctness of our analysis. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Chen, L., & Zhao, H. (2007). Stability of stochastic neutral cellular neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4682 LNAI, pp. 148–156). Springer Verlag. https://doi.org/10.1007/978-3-540-74205-0_17
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