Dynamical behavior for fractional-order shunting inhibitory cellular neural networks
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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.
Share and Cite
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
Keywords
- Shunting inhibitory cellular neural networks
- fractional order
- uniform stability.
MSC
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