An RNN-Based Algorithm for Decentralized-Partial-Consensus Constrained Optimization

This technical note proposes a decentralized-partial-consensus optimization (DPCO) problem with inequality constraints. The partial-consensus matrix originating from the Laplacian matrix is constructed to tackle the partial-consensus constraints. A continuous-time algorithm based on multiple interco...

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Vydáno v:	IEEE transaction on neural networks and learning systems Ročník 34; číslo 1; s. 534 - 542
Hlavní autoři:	Xia, Zicong, Liu, Yang, Qiu, Jianlong, Ruan, Qihua, Cao, Jinde
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Constraints Cost function Decentralized-partial-consensus optimization (DPCO) Learning systems Neural networks Neurodynamics nonsmooth analysis Optimization Optimization methods partial-consensus matrix Recurrent neural networks recurrent neural networks (RNNs) Task analysis
ISSN:	2162-237X, 2162-2388, 2162-2388
On-line přístup:	Získat plný text
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