New results on convergence of fuzzy cellular neural networks with multi-proportional delays

Original Article

Abstract

In this paper, we propose and study the global exponential convergence of a class of fuzzy cellular neural networks with multi-proportional delays, which has not been studied in the existing literature. Applying the differential inequality technique and Lyapunov functional method, we establish a set of global exponential convergence criteria. The sufficient criteria can be easily tested in practice by simple algebra computations. The obtained results play an important role in designing fuzzy neural networks. Moreover, an illustrative example is given to demonstrate our theoretical results.

Keywords

Fuzzy cellular neural network Exponential convergence Proportional delay 

Notes

Acknowledgements

This work was supported by the National Social Science Fund of China (15BJY122), the Humanities and Social Sciences Foundation of Ministry of Education of P. R. China (Grant No. 12YJAZH173). The author is grateful to the editor and referees for their excellent suggestions, which greatly improve our presentation.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsHunan University of CommerceChangshaPeople’s Republic of China

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