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

Risultato della ricerca: Articlepeer review

6 Citazioni (Scopus)

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 preassigned 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)3197-3200
RivistaIEEE Transactions on Magnetics
Volume44
Stato di pubblicazionePublished - 2008

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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