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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/80760

Title:	Multistability for Delayed Neural Networks via Sequential Contracting
Authors:	曾睿彬 Tseng, Jui-Pin Cheng, Chang-Yuan Lin, Kuang-Hui Shih, Chih-Wen
Contributors:	應數系
Date:	2015-12
Issue Date:	2016-01-25 11:12:56 (UTC+8)
Abstract:	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.
Relation:	IEEE Transactions on Neural Networks and Learning Systems, Vol.26, No.12, pp.3109 - 3122
Data Type:	article
DOI 連結:	http://dx.doi.org/10.1109/TNNLS.2015.2404801
DOI:	10.1109/TNNLS.2015.2404801
Appears in Collections:	[應用數學系] 期刊論文

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