کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
409107 | 679053 | 2008 | 14 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Global exponential estimates of stochastic interval neural networks with discrete and distributed delays Global exponential estimates of stochastic interval neural networks with discrete and distributed delays](/preview/png/409107.png)
This paper is concerned with the robust exponential estimating problem for a class of neural networks with discrete and distributed delays. The considered neural networks are disturbed by Wiener processes, and possess interval uncertainties in the system parameters. A sufficient condition, which does not only guarantee the global exponential stability but also provides more exact characterizations on the decay rate and the coefficient, is established in terms of a novel Lyapunov–Krasovskii functional equipped with appropriately constructed exponential terms and the linear matrix inequality (LMI) technique. The estimates of the decay rate and the coefficient are obtained by solving a set of LMIs, which can be implemented easily by effective algorithms. In addition, slack matrices are introduced to reduce the conservatism of the condition. A numerical example is provided to illustrate the effectiveness of the theoretical results.
Journal: Neurocomputing - Volume 71, Issues 13–15, August 2008, Pages 2950–2963