Electronic Resource
[S.l.]
:
American Institute of Physics (AIP)
Journal of Applied Physics
87 (2000), S. 6821-6823
ISSN:
1089-7550
Source:
AIP Digital Archive
Topics:
Physics
Notes:
It has been recently shown that the identification process of scalar, as well as some family of vector, Preisach-type models may be accomplished by the aid of artificial neural networks. Our purpose in this article is to further generalize the approach through which neural networks may be utilized for the identification of vector Preisach models, while using arbitrary measured data for a magnetic recording tape sample. Using the proposed approach, the identification process has been performed and additional simulations have been carried out and compared to corresponding measurements. Comparison results suggest that the proposed technique can lead to good agreement between measured and predicted values. © 2000 American Institute of Physics.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1063/1.372853
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