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Identification of the Parameters of Reduced Vector Preisach Model by Neural Networks

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1 Author(s)
Marco Trapanese ; Dipt. di Ing. Elettr. Elettron. e delle Telecomun., Univ. di Palermo, Palermo

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 preassigned parameters. It is shown how a properly trained network is able to find the parameters needed to best fit a magnetization hysteresis curve.

Published in:

IEEE Transactions on Magnetics  (Volume:44 ,  Issue: 11 )