Hybrid Method for Inverse Electromagnetic Coil Optimization Using Multi-transition and Hopfield Neural Networks

Yamamoto, Takeyoshi and Cingoski, Vlatko and Kaneda, Kazufumi and Yamashita, Hideo (1996) Hybrid Method for Inverse Electromagnetic Coil Optimization Using Multi-transition and Hopfield Neural Networks. In: Nonlinear Electromagnetic Systems.

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Abstract

In this paper, a hybrid method for inverse optimization of electromagnetic coils utilizing the multi-transition neural network and the Hopfield neural network is proposed. Due to the discrete character of the neural network, an optimization problem is transformed into a discrete problem through the division of the entire coil area into elemental coils with constant current density. The minimization of the objective function is performed by the multi-transition neural network and the Hopfield neural network in turns. Subdivision of the elemental coils is performed in order to achieved better accuracy of the results which are verified using 2-D finite element analysis. The application of the proposed method for inverse optimization of MRI device is also presented.

Item Type: Conference or Workshop Item (Paper)
Subjects: Engineering and Technology > Electrical engineering, electronic engineering, information engineering
Divisions: Faculty of Electrical Engineering
Depositing User: Vlatko Cingoski
Date Deposited: 19 Dec 2012 15:12
Last Modified: 01 Oct 2013 12:01
URI: http://eprints.ugd.edu.mk/id/eprint/4048

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