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A CAD Based Approach On Artificial Neural Networks For Conductor Backed Coplanar Waveguides

Author(s): Shanmuganantham T | Raghavan S

Journal: IETE Journal of Research
ISSN 0377-2063

Volume: 54;
Issue: 2;
Start page: 121;
Date: 2008;
Original page

In This paper a computer aided design (CAD) approach based on artificial neural networks (ANNs) successfully simulated to determine the characteristics parameters such a effective dielectric constant and characteristic impedances of conductor backed coplanar wave guides (CBCPW). These neural models are trained with Levenberg-Marquardt, Bayesian regularization, gradient descent algorithms. The Levenberg-Marquardt algorithm and Bayesian regularization was found to be the best algorithm among all the three algorithms. As a result, ANN models presented in this work can be used easily, simply and accurately to determine the characteristic parameters of the conductor Backed Coplanar Wave guides.
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