Computational modeling of GMI effect in Co-based amorphous ribbons

This paper presents a prediction of a giant magneto-impedance (GMI) effect on Co-based amorphous ribbons using an artificial neural network (ANN) approach based on a self-organizing feature map (SOFM). The input parameters included the compositions of Fe and Co, ribbon width and magnetizing frequenc...

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Bibliographic Details
Published in:	Journal of inequalities and applications Vol. 2013; no. 1
Main Author:	Kaya, Asli Ayten
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 14-06-2013
Subjects:	Analysis Applications of Mathematics Mathematics Mathematics and Statistics Proceedings of the International Congress in Honour of Professor Hari M. Srivastava giant magneto-impedance effect neural network modeling
Online Access:	Get full text
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Summary:	This paper presents a prediction of a giant magneto-impedance (GMI) effect on Co-based amorphous ribbons using an artificial neural network (ANN) approach based on a self-organizing feature map (SOFM). The input parameters included the compositions of Fe and Co, ribbon width and magnetizing frequency. The output parameter was the GMI effect. The results show that the proposed model can be used for estimation of the GMI effect in the amorphous ribbons.
ISSN:	1029-242X 1029-242X
DOI:	10.1186/1029-242X-2013-293