Two-Timescale Multilayer Recurrent Neural Networks for Nonlinear Programming

This article presents a neurodynamic approach to nonlinear programming. Motivated by the idea of sequential quadratic programming, a class of two-timescale multilayer recurrent neural networks is presented with neuronal dynamics in their output layer operating at a bigger timescale than in their hid...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 33; H. 1; S. 37 - 47
Hauptverfasser:	Wang, Jiasen, Wang, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Global optimization Mathematical model Multilayers Neural networks Neurodynamic optimization Neurodynamics Nonhomogeneous media Nonlinear programming Programming Quadratic programming Recurrent neural networks Time two-timescale system
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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