Anti-periodic solution for fuzzy Cohen–Grossberg neural networks with time-varying and distributed delays
Articles
Yongkun Li
Yunnan University, China
Li Yang
Yunnan University, China
Wanqin Wu
Yunnan Nationalities University, China
Published 2015-07-20
https://doi.org/10.15388/NA.2015.3.6
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Keywords

Cohen Grossberg neural networks
exponential stability
anti-periodic solutions
coincidence degree

How to Cite

Li, Y., Yang, L. and Wu, W. (2015) “Anti-periodic solution for fuzzy Cohen–Grossberg neural networks with time-varying and distributed delays”, Nonlinear Analysis: Modelling and Control, 20(3), pp. 395–416. doi:10.15388/NA.2015.3.6.

Abstract

In this paper, by using a continuation theorem of coincidence degree theory and a differential inequality, we establish some sufficient conditions ensuring the existence and global exponential stability of anti-periodic solutions for a class of fuzzy Cohen–Grossberg neural networks with time-varying and distributed delays. In addition, we present an illustrative example to show the feasibility of obtained results.

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