Novel robust stability criteria for stochastic hopfield neural network with time-varying delays

Authors:
Xiaolin Li;Minrui Wang
Affiliations:
Department of Mathematics, Shanghai University, Shanghai, China;Department of Mathematics, Shanghai University, Shanghai, China
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Year:
2012

Citing 6
Cited 0

Stability of stochastic neural networks

Neural, Parallel & Scientific Computations
An analysis of exponential stability of delayed neural networks with time varying delays

Neural Networks
Robust stability analysis of generalized neural networks with multiple discrete delays and multiple distributed delays

Neurocomputing
Stochastic robust stability of markovian jump nonlinear uncertain neural networks with wiener process

ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
A generalized LMI-based approach to the global asymptotic stability of delayed cellular neural networks

IEEE Transactions on Neural Networks
Global Asymptotical Stability of Recurrent Neural Networks With Multiple Discrete Delays and Distributed Delays

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, stochastic Hopfield neural networks with time-varying delays are investigated based on Lyapunov-krasovskii functional approach and linear matrix inequality(LMI) technique. The proposed criterion is expressed in terms of linear matrix inequality(LMI)and is less conservative than some existing ones and can be effectively solved by Matlab LMI toolbox. A numerical example that confirms the theoretical result is also presented.