Stability analysis of recurrent neural networks with distributed delays satisfying lebesgue-stieljies measures

Authors:
Zhanshan Wang;Huaguang Zhang;Jian Feng
Affiliations:
School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, People's Republic of China;School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, People's Republic of China;School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, People's Republic of China
Venue:
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Year:
2010

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Abstract

Global asymptotic stability problem for a class of recurrent neural networks with a general class of distributed delays has been studied based on distributed-delay-matrix decomposition method and linear matrix inequality (LMI) technique The proposed stability criterion is suitable for a general class of multiple delayed recurrent neural networks Especially, for the recurrent neural networks with different multiple delays, infinite distributed delays and finite distributed delays, we have also established corresponding LMI-based stability criteria, which are simple in expression form and easy to check Compared with the existing results, our results are new and can be regarded as an alterative of M-matrix based stability results in the literature ...