Smoothed \(L_{1/2}\) regularizer learning for split-complex valued neuro-fuzzy algorithm for TSK system and its convergence results

DOI10.1016/j.jfranklin.2018.06.015zbMath1451.93213OpenAlexW2809570911MaRDI QIDQ1661977

Y. Aharonov

Publication date: 17 August 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2018.06.015

zbMATH Keywords

smoothed \(L_{1/2}\) regularizersplit-complex valued neuro-fuzzy algorithmTakagi-Sugeno-Kang system

Mathematics Subject Classification ID

Fuzzy control/observation systems (93C42) Networked control (93B70)

Related Items (1)

Deterministic convergence analysis via smoothing group Lasso regularization and adaptive momentum for Sigma-Pi-Sigma neural network

Uses Software

• ANCFIS
• Fuzzy ARTMAP

Cites Work

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