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Finite-time Mittag-Leffler synchronization of fractional-order delayed memristive neural networks with parameters uncertainty and discontinuous activation functions
作者姓名:陈冲  丁芝侠  李赛  王利恒
作者单位:Hubei Key Laboratory of Optical Information and Pattern Recognition
基金项目:Project supported by the National Natural Science Foundation of China(Grant Nos.61703312 and 61703313)。
摘    要:The finite-time Mittag-Leffler synchronization is investigated for fractional-order delayed memristive neural networks(FDMNN)with parameters uncertainty and discontinuous activation functions.The relevant results are obtained under the framework of Filippov for such systems.Firstly,the novel feedback controller,which includes the discontinuous functions and time delays,is proposed to investigate such systems.Secondly,the conditions on finite-time Mittag-Leffler synchronization of FDMNN are established according to the properties of fractional-order calculus and inequality analysis technique.At the same time,the upper bound of the settling time for Mittag-Leffler synchronization is accurately estimated.In addition,by selecting the appropriate parameters of the designed controller and utilizing the comparison theorem for fractional-order systems,the global asymptotic synchronization is achieved as a corollary.Finally,a numerical example is given to indicate the correctness of the obtained conclusions.

关 键 词:FRACTIONAL-ORDER  DELAYED  memristive  neural  networks(FDMNN)  parameters  uncertainty  DISCONTINUOUS  activation  functions  FINITE-TIME  Mittag-Leffler  SYNCHRONIZATION

Finite-time Mittag-Leffler synchronization of fractional-order delayed memristive neural networks with parameters uncertainty and discontinuous activation functions
Chong Chen,Zhixia Ding,Sai Li,Liheng Wang.Finite-time Mittag-Leffler synchronization of fractional-order delayed memristive neural networks with parameters uncertainty and discontinuous activation functions[J].Chinese Physics B,2020(4):127-138.
Authors:Chong Chen  Zhixia Ding  Sai Li  Liheng Wang
Institution:(Hubei Key Laboratory of Optical Information and Pattern Recognition,School of Electrical and Information Engineering,Wuhan Institute of Technology,Wuhan 430205,China)
Abstract:
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