Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Novel robust stability criteria for stochastic Hopfield neural networks with time delays|
|Citation:||IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 2009; 39(2):467-474|
|Publisher:||IEEE-Inst Electrical Electronics Engineers Inc|
|Rongni Yang, Huijun Gao, and Peng Shi|
|Abstract:||In this paper, the problem of asymptotic stability for stochastic Hopfield neural networks (HNNs) with time delays is investigated. New delay-dependent stability criteria are presented by constructing a novel Lyapunov-Krasovskii functional. Moreover, the results are further extended to the delayed stochastic HNNs with parameter uncertainties. The main idea is based on the delay partitioning technique, which differs greatly from most existing results and reduces conservatism. Numerical examples are provided to illustrate the effectiveness and less conservativeness of the developed techniques.|
|Rights:||© 2008 IEEE|
|Appears in Collections:||Electrical and Electronic Engineering publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.