A CAD approach based on artificial neural networks for conductor- backed edge coupled coplanar waveguides

In this paper, a new conformal mapping quasi static approximation method based on ANNs is used to calculate accurately the odd-and even-mode characteristic impedances, coupling coefficient and effective permittivities of CB-ECCPWs. ANNs have been recently recognized as a fast and flexible tool for RF and microwave modeling, analysis and design. ANN models are developed from measured or simulated microwave data training process. Resulting ANN models are used in place of CPU-intensive theoretical for fast accurate microwave design, analysis and optimization. The ANN employed in this paper is the MLPNN. Four learning algorithms BR, LM, QN and SCG are used to train the MLPNNs. These learning algorithms are employed to obtain better performance and faster convergence with simpler structure.