Identification of parameters of dynamic Preisach model by neural networks

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Abstract

This paper presents a methodology for identifying Reduced Vector Preisach Model parameters by using neural networks. The neural network used is a multiplayer perceptron trained with the Levenberg-Marquadt training algorithm. The network is trained by some hysteresis data, which are generated by using Reduced Vector Preisach Model with pre-assigned parameters. It is shown how a properly trained network is able to find the parameters needed to best fit a magnetization hysteresis curve.
Lingua originaleEnglish
pagine (da-a)07D929-1-07D929-3
RivistaJournal of Applied Physics
Volume103
Stato di pubblicazionePublished - 2008

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All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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