A neural network inversion algorithm for electromagnetic device design

Iliana Marinova; Christo Panchev; D Katsakos

doi:10.1109/20.877628

A neural network inversion algorithm for electromagnetic device design

Iliana Marinova, Christo Panchev, D Katsakos

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

In this paper we present a new model that employs, in a natural and effective way, a neural network inversion algorithm providing a solution of the electromagnetic device design problem. The model combines two types of artificial neural networks and applies a neural network inversion algorithm. Further development of this model can propose an efficient solution to the electromagnetic device design problem. The model is applied to the magnetic stimulation coil design as well as gradient coil design. The results obtained show the effectiveness of the proposed model

Original language	English
Pages (from-to)	1080-1084
Number of pages	5
Journal	IEEE Transactions on Magnetics
Volume	36
Issue number	4
DOIs	https://doi.org/10.1109/20.877628
Publication status	Published - Jul 2000
Externally published	Yes

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title = "A neural network inversion algorithm for electromagnetic device design",

abstract = "In this paper we present a new model that employs, in a natural and effective way, a neural network inversion algorithm providing a solution of the electromagnetic device design problem. The model combines two types of artificial neural networks and applies a neural network inversion algorithm. Further development of this model can propose an efficient solution to the electromagnetic device design problem. The model is applied to the magnetic stimulation coil design as well as gradient coil design. The results obtained show the effectiveness of the proposed model",

author = "Iliana Marinova and Christo Panchev and D Katsakos",

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AU - Marinova, Iliana

AU - Panchev, Christo

AU - Katsakos, D

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N2 - In this paper we present a new model that employs, in a natural and effective way, a neural network inversion algorithm providing a solution of the electromagnetic device design problem. The model combines two types of artificial neural networks and applies a neural network inversion algorithm. Further development of this model can propose an efficient solution to the electromagnetic device design problem. The model is applied to the magnetic stimulation coil design as well as gradient coil design. The results obtained show the effectiveness of the proposed model

AB - In this paper we present a new model that employs, in a natural and effective way, a neural network inversion algorithm providing a solution of the electromagnetic device design problem. The model combines two types of artificial neural networks and applies a neural network inversion algorithm. Further development of this model can propose an efficient solution to the electromagnetic device design problem. The model is applied to the magnetic stimulation coil design as well as gradient coil design. The results obtained show the effectiveness of the proposed model

U2 - 10.1109/20.877628

DO - 10.1109/20.877628

M3 - Article

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VL - 36

SP - 1080

EP - 1084

JO - IEEE Transactions on Magnetics

JF - IEEE Transactions on Magnetics

IS - 4

ER -

A neural network inversion algorithm for electromagnetic device design

Abstract

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