Stability analysis for stochastic BAM neural networks with distributed time delays

Authors:
Guanjun Wang
Affiliations:
Department of Mathematics, Southeast University, Nanjing, China
Venue:
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Year:
2010

Citing 4
Cited 0

Bidirectional associative memories

IEEE Transactions on Systems, Man and Cybernetics
Global exponential stability of bidirectional associative memory neural networks with distributed delays

Journal of Computational and Applied Mathematics
Stability analysis for stochastic BAM neural networks with Markovian jumping parameters

Neurocomputing
Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper is concerned with the stability problem for stochastic bidirectional associative memory neural networks with distributed time delays By applying the Lyapunov functional method, the semimartingale convergence theorem, and some inequality techniques, some sufficient conditions are derived to guarantee the almost sure exponential stability of the system One example is provided at the end of this paper to show the effectiveness of our results.