Robust stability analysis of interval fuzzy Cohen-Grossberg neural networks with piecewise constant argument of generalized type

Neural Networks : the Official Journal of the International Neural Network Society
Gang BaoZhigang Zeng

Abstract

In this paper, existence and uniqueness of the solution of interval fuzzy Cohen-Grossberg neural networks with piecewise constant argument are discussed. Based on the comparison principle, it presents new theoretical results on the global robust exponential stability of interval fuzzy Cohen-Grossberg networks with piecewise constant argument. As a special case, the corresponding results of interval fuzzy recurrent neural networks with piecewise constant argument are derived. Three examples are given for illustrating validity of the obtained results.

References

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Mar 29, 2003·Neural Networks : the Official Journal of the International Neural Network Society·Jinde Cao, Dongming Zhou
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Citations

Nov 13, 2013·Neural Networks : the Official Journal of the International Neural Network Society·Shiping WenTingwen Huang
Apr 5, 2014·Neural Networks : the Official Journal of the International Neural Network Society·Zhenyuan GuoZheng Yan
Mar 19, 2014·Neural Networks : the Official Journal of the International Neural Network Society·Sabri Arik
Mar 22, 2014·Neural Networks : the Official Journal of the International Neural Network Society·Xian-Ming Zhang, Qing-Long Han
Sep 19, 2014·Neural Networks : the Official Journal of the International Neural Network Society·Wei HuangWitold Pedrycz
Sep 8, 2017·IEEE Transactions on Neural Networks and Learning Systems·Wengui YangJinde Cao
Jun 23, 2019·Sensors·Yirga Yayeh MunayeGetaneh Berie Tarekegn

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