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Multistability for Delayed Neural Networks via Sequential Contracting
Ist Teil von
IEEE transaction on neural networks and learning systems, 2015-12, Vol.26 (12), p.3109-3122
Ort / Verlag
United States: IEEE
Erscheinungsjahr
2015
Quelle
IEEE Xplore Digital Library
Beschreibungen/Notizen
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 piecewise-linear activation functions. Several numerical examples illustrate the present analytic theory.