Dynamical behavior for fractional-order shunting inhibitory cellular neural networks


Authors

Yang Zhao - Department of Mechanical and Electrical Engineering, Guangdong University of Science and Technology, Dongguan 523083, P. R. China. Yanguang Cai - School of Automation, Guangdong University of Technology, Guangzhou 510006, P. R. China. Guobing Fan - Department of Basic Subjects, Hunan University of Finance and Economics, Changsha 410205, P. R. China.


Abstract

This paper deals with a class of fractional-order shunting inhibitory cellular neural networks. Applying the contraction mapping principle, Krasnoselskii fixed point theorem and the inequality technique, some very verifiable criteria on the existence and uniqueness of nontrivial solution are obtained. Moreover, we also investigate the uniform stability of the fractional-order shunting inhibitory cellular neural networks. Finally, an example is given to illustrate our main theoretical findings. Our results are new and complement previously known results.


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ISRP Style

Yang Zhao, Yanguang Cai, Guobing Fan, Dynamical behavior for fractional-order shunting inhibitory cellular neural networks, Journal of Nonlinear Sciences and Applications, 9 (2016), no. 6, 4589--4599

AMA Style

Zhao Yang, Cai Yanguang, Fan Guobing, Dynamical behavior for fractional-order shunting inhibitory cellular neural networks. J. Nonlinear Sci. Appl. (2016); 9(6):4589--4599

Chicago/Turabian Style

Zhao, Yang, Cai, Yanguang, Fan, Guobing. "Dynamical behavior for fractional-order shunting inhibitory cellular neural networks." Journal of Nonlinear Sciences and Applications, 9, no. 6 (2016): 4589--4599


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