Affiliation:
1. School of Computer Science, Huainan Normal University, Huainan 232038, China
2. School of Finance and Mathematics, Huainan Normal University, Huainan 232038, China
Abstract
This paper investigates a class of finite-time synchronization problems of fractional order fuzzy inertial cellular neural networks (FFICNNs) with piecewise activations and mixed delays. First, the Caputo FFICNNs are established. A suitable transformation variable is constructed to rewrite FFICNNs with mixed delays into a first-order differential system. Secondly, some new effective criteria are constructed on the basis of the finite-time stability theory and Lyapunov functionals to realize the synchronization of the drive-response system. Finally, two numerical simulation examples show that the proposed method is effective.
Funder
Natural Science Foundation of Anhui Province
Program for Innovative Research Team in Universities of Anhui Province
University Natural Science Foundation of Anhui Province
National Natural Science Foundation of China
Research and Development Plan Project Foundation of Huainan
Subject
Statistics and Probability,Statistical and Nonlinear Physics,Analysis
Reference43 articles.
1. The global stability of fuzzy cellular neural network;Yang;IEEE Trans. Circuits Syst. I,1996
2. Yang, T., Yang, L., Wu, C.W., and Chua, L.O. (1996, January 24–26). Fuzzy cellular neural networks: Applications. Proceedings of the 1996 Fourth IEEE International Workshop on Cellular Neural Networks and Their Applications Proceedings (CNNA-96), Seville, Spain.
3. Fuzzy cellular neural network: A new paradigm for image processing;Yang;Int. J. Circ. Theory Appl.,1997
4. A new detection algorithm (NDA) based on fuzzy cellular neural networks for white blood cell detection;Shitong;IEEE Trans. Inf. Technol. Biomed.,2006
5. Advanced fuzzy cellular neural network: Application to CT liver images;Wang;Artif. Intell. Med.,2007
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