Neuromodeling of microwave circuits exploiting space mapping technology

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Miniatura

Fecha

1999-12

Autores

Bandler, John W.
Ismail, Mostafa A.
Rayas-Sánchez, José E.
Zhang, Qi J.

Título de la revista

ISSN de la revista

Título del volumen

Editor

IEEE Trans. Microwave Theory Tech;47

Resumen

Descripción

For the first time, we present modeling of microwave circuits using artificial neural networks (ANN’s) based on space-mapping (SM) technology. SM-based neuromodels decrease the cost of training, improve generalization ability, and reduce the complexity of the ANN topology with respect to the classical neuromodeling approach. Five creative techniques are proposed to generate SM-based neuromodels. A frequencysensitive neuromapping is applied to overcome the limitations of empirical models developed under quasi-static conditions. Huber optimization is used to train the ANN’s. We contrast SM-based neuromodeling with the classical neuromodeling approach as well as with other state-of-the-art neuromodeling techniques. The SMbased neuromodeling techniques are illustrated by a microstrip bend and a high-temperature superconducting filter.

Palabras clave

Neuromodeling, Computer Aided Design (CAD), Design Automation, Microstrip Filters, Microwave Circuits, Neural Network Applications, Neural Space Mapping (NSM), Optimization Methods, Space Mapping

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