Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1816964 | Physica B: Condensed Matter | 2006 | 5 Pages |
Abstract
In this paper, we present a neural network-based approach, which allows us to predict the hysteretic loop, whatever the value of the frequency and flux density. The approach makes use of the Preisach-hysteretic model (PM) which provides a mathematical model to the B(H)B(H) curve, while the neural enables us to identify and predict the behaviour of parameters that the PM needs.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Condensed Matter Physics
Authors
D. Moussaoui, A. Bendjerad, M. Oussalah, H. Houassine,