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PIER PIER B PIER C PIER M PIER Letters PIER Photonics
2008-04-11
Adaptive Neuro-Fuzzy Inference System for the Computation of the Characteristic Impedance and the Effective Permittivity of the Micro-Coplanar Strip Line
By
Nurcan Sarikaya,

    Dr. Nurcan Sarikaya

    Department of Electronic Engineering

    Erciyes University

    Turkey

    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, 225-237, 2008
doi:10.2528/PIERB08031223 | Google Scholar

Abstract
A method based on adaptive neuro-fuzzy inference system (ANFIS) for computing the effective permittivity and the characteristic impedance of the micro-coplanar strip (MCS) line is presented. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems (FISs). A hybrid learning algorithm, which combines the least square method and the backpropagation algorithm, is used to identify the parameters of ANFIS. The effective permittivity and the characteristic impedance results obtained by using ANFIS are in good agreement with the theoretical and experimental results reported elsewhere.
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Citation
Nurcan Sarikaya, Kerim Guney, and Celal Yildiz, "Adaptive Neuro-Fuzzy Inference System for the Computation of the Characteristic Impedance and the Effective Permittivity of the Micro-Coplanar Strip Line," Progress In Electromagnetics Research B, Vol. 6, 225-237, 2008.
doi:10.2528/PIERB08031223
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