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.
|Rivista||Journal of Applied Physics|
|Stato di pubblicazione||Published - 2008|
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