Neuromodeling of microwave circuits exploiting space mapping technology
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Fecha
1999-12
Autores
Bandler, John W.
Ismail, Mostafa A.
Rayas-Sánchez, José E.
Zhang, Qi J.
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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