Global Stability Analysis for Complex-Valued Recurrent Neural Networks and Its Application to Convex Optimization Problems

Abstract

INTrODUCTION Recurrent neural networks whose neurons are fully interconnected have been utilized to implement associative memories and solve optimization problems. These networks are regarded as nonlinear dynamical feedback systems. Stability properties of this class of dynamical networks are an important issue from applications point of view. ABSTrACT… (More)

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@inproceedings{Mori2010GlobalSA, title={Global Stability Analysis for Complex-Valued Recurrent Neural Networks and Its Application to Convex Optimization Problems}, author={Takehiro Mori}, year={2010} }