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PIER PIER B PIER C PIER M PIER Letters PIER Photonics
2008-04-08
Neural Models for the Elliptic- and Circular-Shaped Microshield Lines
By
Sabri Kaya,

    Dr. Sabri Kaya

    Department of Electronic Engineering

    Erciyes University

    Turkey

    Homepage

Mustafa Turkmen,

    Prof. Mustafa Turkmen

    Department of Electrical and Computer Engineering

    Boston University

    USA

    Homepage

Kerim Guney,

    Professor Kerim Guney

    Faculty of Engineering

    Nuh Naci Yazgan University

    Turkey

    Homepage

Celal Yildiz

    Dr. Celal Yildiz

    Department of Electronic Engineering

    Erciyes University

    Turkey

    Homepage

Progress In Electromagnetics Research B, Vol. 6, 169-181, 2008
doi:10.2528/PIERB08031216 | Google Scholar

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.
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Citation
Sabri Kaya, Mustafa Turkmen, Kerim Guney, and 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
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