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    政大機構典藏 > 理學院 > 應用數學系 > 期刊論文 >  Item 140.119/80760


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    題名: Multistability for Delayed Neural Networks via Sequential Contracting
    作者: 曾睿彬
    Tseng, Jui-Pin
    Cheng, Chang-Yuan
    Lin, Kuang-Hui
    Shih, Chih-Wen
    貢獻者: 應數系
    日期: 2015-12
    上傳時間: 2016-01-25 11:12:56 (UTC+8)
    摘要: In this paper, we explore a variety of new multistability scenarios in the general delayed neural network system. Geometric structure embedded in equations is exploited and incorporated into the analysis to elucidate the underlying dynamics. Criteria derived from different geometric configurations lead to disparate numbers of equilibria. A new approach named sequential contracting is applied to conclude the global convergence to multiple equilibrium points of the system. The formulation accommodates both smooth sigmoidal and piecewiselinear activation functions. Several numerical examples illustrate the present analytic theory.
    關聯: IEEE Transactions on Neural Networks and Learning Systems, Vol.26, No.12, pp.3109 - 3122
    資料類型: article
    DOI 連結: http://dx.doi.org/10.1109/TNNLS.2015.2404801
    DOI: 10.1109/TNNLS.2015.2404801
    顯示於類別:[應用數學系] 期刊論文

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