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2008-04-08
Neural Models for the Elliptic- and Circular-Shaped Microshield Lines
By
Progress In Electromagnetics Research B, Vol. 6, 169-181, 2008
Abstract
This article presents a new approach based on artificial neural networks (ANNs) to calculate the characteristic parameters of elliptic and circular-shaped microshield lines. Six learning algorithms, bayesian regularization (BR), Levenberg-Marquardt (LM), quasi-Newton (QN), scaled conjugate gradient (SCG), resilient propagation (RP), and conjugate gradient of Fletcher-Reeves (CGF), are used to train the ANNs. The neural results are in very good agreement with the results reported elsewhere. When the performances of neural models are compared with each other, the best and worst results are obtained from the ANNs trained by the BR and CGF algorithms, respectively.
Citation
Sabri Kaya Mustafa Turkmen Kerim Guney Celal Yildiz , "Neural Models for the Elliptic- and Circular-Shaped Microshield Lines," Progress In Electromagnetics Research B, Vol. 6, 169-181, 2008.
doi:10.2528/PIERB08031216
http://www.jpier.org/PIERB/pier.php?paper=08031216
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