A new neural network technique for the design of multilayered microwave shielded bandpass filters
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URI: https://onlinelibrary.wiley.com/doi/abs/10.1002/mmce.20363URI: http://hdl.handle.net/10317/8499
ISSN: 1096-4290
DOI: 10.1002/mmce.20363
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Pascual García, Juan; Quesada Pereira, Fernando Daniel; Cañete Rebenaque, David; Gómez Díaz, Juan Sebastián; Álvarez Melcón , AlejandroGrupo de investigación
Grupo Electromagnetismo Aplicado a las TelecomunicacionesÁrea de conocimiento
Teoría de la Señal y las ComunicacionesFecha de publicación
2009-05Editorial
John WileyCita bibliográfica
García, J.P., Pereira, F.Q., Rebenaque, D.C., Díaz, J.S.G. and Melcón, A.Á. (2009), A new neural network technique for the design of multilayered microwave shielded bandpass filters. Int J RF and Microwave Comp Aid Eng, 19: 405-415. doi:10.1002/mmce.20363Palabras clave
Neural NetworksMicrowave filters
Microstrip fliters
Filter design techniques
Resumen
In this work, we propose a novel technique based on neural networks, for the design of microwave filters in shielded printed technology. The technique uses radial basis function neural networks to represent the non linear relations between the quality factors and coupling coefficients, with the geometrical dimensions of the resonators. The radial basis function neural networks are employed for the first time in the design task of shielded printed filters, and permit a fast and precise operation with only a limited set of training data. Thanks to a new cascade configuration, a set of two neural networks provide the dimensions of the complete filter in a fast and accurate way. To improve the calculation of the geometrical dimensions, the neural networks can take as inputs both electrical parameters and physical dimensions computed by other neural networks. The neural network technique is combined with gradient based optimization methods to further improve the response of the filters. Results are ...
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