An \(H_\infty\) control approach to robust learning of feedforward neural networks

DOI10.1016/J.NEUNET.2011.03.015zbMath1263.93070OpenAlexW2050069736WikidataQ46530156 ScholiaQ46530156MaRDI QIDQ1952560

Xing Jian Jing

Publication date: 31 May 2013

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2011.03.015

zbMATH Keywords

\(H_\infty\) controllinear matrix inequality (LMI)estimation error\(H_\infty\)-learning algorithmfeedforward neural network (FNN)predefined \(H_\infty\) noise attenuation levelrobust controller design problem

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) (H^infty)-control (93B36)

Related Items (3)

Robust adaptive learning of feedforward neural networks via LMI optimizations ⋮ Control-based algorithms for high dimensional online learning ⋮ Extended dissipative learning of time-delay recurrent neural networks

Cites Work

• An LMI Approach to Stability of Systems With Severe Time-Delay
• Unnamed Item

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