Modeling switched circuits based on wavelet decomposition and neural networks

DOI10.1016/j.jfranklin.2010.01.004zbMath1298.94155OpenAlexW2017591845MaRDI QIDQ468244

Yakup Demir, Ibrahim Turkoglu, Davut Hanbay

Publication date: 6 November 2014

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

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2010.01.004

zbMATH Keywords

nonlinear systemsneural networkswavelet decompositionswitched circuits

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Numerical methods for wavelets (65T60) Analytic circuit theory (94C05)

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Cites Work

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• Derivation of state and output equations for systems containing switches and a novel definition of a switch using the bond graph model
• Examination of chaotic behaviours using bond graph model.
• Nonregressivity in switched linear circuits and mechanical systems
• Modelling and simulation with neural and fuzzy‐neural networks of switched circuits
• Efficient transient simulation of interconnect networks
• Learning of Chua's circuit attractors by locally recurrent neural networks

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