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.
|Rivista||IEEE Transactions on Magnetics|
|Stato di pubblicazione||Published - 2008|
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Electrical and Electronic Engineering