Neural Network Based Characterizing Parameters of Coplanar Waveguides
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| Title | Neural Network Based Characterizing Parameters of Coplanar Waveguides |
| Authors | |
| Abstract | Artificial neural networks (ANNs) has been a promising tool for microwave modeling, simulation and optimization. In this paper we present the estimation of characteristic parameters of top shielded multilayer coplanar wave-guides(MPCWs) using ANN model. For training the model is done with Levenberg-Marquardt algorithm. Our result shows that the neural network successfully calculates characteristic parameters of top shielded Microwave coplanar waveguides with the high accuracy (error is just about 0.05%). Using these models one can calculate effective relative permitivity and the characteristic impedance of the top shielded MCPWs without possessing strong background knowledge. Even if training takes a few minutes, the test process only takes a few microseconds to produce εeff and Z0 after training. It should also be emphasized that both parameters can be determined from one neural model. |
| Publisher | Indian Society for Education and Environment (ISEE) |
| Date | 2010-03-01 |
| Source | Indian Journal of Science and Technology Volume 3, Issue 3, March 2010 |