The minimum gradient complexity control applied to sensitivity extraction of electromagnetic devices

D. A G Vieira, J. A. Vasconcelos, V. Palade, W. M. Caminhas

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Abstract

This paper applies the parallel layer perceptron network trained with the minimum gradient method (PLP-MGM) to the problem of indirect sensitivity extraction of electromagnetic devices. The networks trained with the MGM are less dependent of users' defined parameters, as, for instance, the number of neurons. Some results are presented considering the indirect sensitivity extraction of a loudspeaker magnet assembly unit and an inverse scattering problem, and they show the effectiveness of the proposed approach.

Original languageEnglish
Article number4527018
Pages (from-to)1114-1117
Number of pages4
JournalIEEE Transactions on Magnetics
Volume44
Issue number6
DOIs
Publication statusPublished - Jun 2008
Externally publishedYes

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Keywords

  • Neural networks
  • Optimization and design
  • Parallel layer perceptron
  • Regularization methods

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Physics and Astronomy (miscellaneous)

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