Finite-Time Stability Analysis of FractionalOrder Delayed Memristive Neural Networks

Li Ruo-Xia; Cao Jin-De

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Finite-Time Stability Analysis of FractionalOrder Delayed Memristive Neural Networks

Li Ruo-Xia, Cao Jin-De

Department of Mathematics, University of Southeast, Nanjing 210096

*Correspondence author

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Funding: The Specialized Research Fund for the Doctoral Program of Higher Education （No.20110092110017）, National Natural Science Foundationof China under Grant nos. (61573096) and （No.61272530）, Natural Science Foundation of Jiangsu Provinceof China （No.BK2012741）, the ``333 Engineering' Foundation of Jiangsu Province of China （No.BRA2015286）, and the Scientific and Technological Research Program of Chongqing Municipal EducationCommission（No. KJ1501002）

Opened online:25 November 2015

Accepted by: none

Citation: Li Ruo-Xia, Cao Jin-De.Finite-Time Stability Analysis of FractionalOrder Delayed Memristive Neural Networks[OL]. [25 November 2015] http://en.paper.edu.cn/en_releasepaper/content/4663059

In this paper, the finite-time stability test procedure fornon-autonomous and autonomous fractional order memristive systemswith a pure time delay and commensurate order between 0 and 1 isproposed. First, two appropriate concepts of the finite-timestability for the mentioned systems with and without external inputare introduced. Then, a sufficient condition for finite-timestability of the underlying systems is derived in the frame of someuseful inequalities and appropriate property of the norm. Inparticular, the sufficient conditions are obtained in terms oflinear inequalities, which turn out to be more efficient from thecomputational point of view. Simulation results are given toillustrate the validity of the theoretical results.

Keywords:Memristive neural networks; fractional-order; finite-time stability;non-autonomous system; autonomous system.

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