Journal
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
Volume 39, Issue 2, Pages 467-474Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMCB.2008.2006860
Keywords
Hopfield neural networks (HNNs); Lyapunov-Krasovskii functional; robust stability; stochastic systems; time delay; uncertainties
Categories
Funding
- National Natural Science Fundation of China [60504008, 60825303]
- Research Fund for the Doctoral Program of Higher Education of China [20070213084]
- EPSRC, U.K. [EP/F029195]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available