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) |
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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: | https://eprints.ugd.edu.mk/id/eprint/4048 |
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