Artificial neural networks for accurate microwave CAD applications

Artificial neural networks for accurate microwave CAD applications

A unique approach for applying neurocomputing technology for accurate CAD of microwave circuits is described. In our proposed method, a multilayer perceptron neural network (MLPNN) is trained to predict the scattering parameters of MMIC passive elements based on the element's physical dimension...

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Bibliographische Detailangaben
Hauptverfasser: Creech, G.L., Paul, B., Lesniak, C., Jenkins, T., Lee, R., Calcatera, M.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial neural networks
Electromagnetic analysis
Microwave circuits
Microwave technology
MMICs
Multi-layer neural network
Multilayer perceptrons
Neural networks
Performance analysis
Scattering parameters
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Beschreibung
Zusammenfassung:A unique approach for applying neurocomputing technology for accurate CAD of microwave circuits is described. In our proposed method, a multilayer perceptron neural network (MLPNN) is trained to predict the scattering parameters of MMIC passive elements based on the element's physical dimensions. The s-parameters were obtained by performing a full-wave electromagnetic (EM) analysis of these elements. An X-band MLPNN spiral inductor model is developed. The MLPNN computed s-parameter values are in excellent agreement with those obtained from EM simulations with correlations greater than 0.99 for all modelled parameters.
ISSN:0149-645X
2576-7216
DOI:10.1109/MWSYM.1996.511043