In this work, a hybrid neural model (HNM) able to characterize accurately the dispersion behavior of the fundamental TE10 mode of a single layer SIW waveguide, is developed. The HNM combines the analytical expression that models the dispersion characteristics of this guiding structure, with a Multi Layer Perceptron Neural Network (MLPNN) which operates as an estimator of the cutoff angular frequency ωt of the fundamental mode. The comparison among HNM computations, numerical results obtained with methods proposed in literature and full-wave data validate both the accuracy and the effectiveness of the proposed approach.

A hybrid neural model for the characterization of a single layer SIW waveguide

ANGIULLI, Giovanni
;
2013

Abstract

In this work, a hybrid neural model (HNM) able to characterize accurately the dispersion behavior of the fundamental TE10 mode of a single layer SIW waveguide, is developed. The HNM combines the analytical expression that models the dispersion characteristics of this guiding structure, with a Multi Layer Perceptron Neural Network (MLPNN) which operates as an estimator of the cutoff angular frequency ωt of the fundamental mode. The comparison among HNM computations, numerical results obtained with methods proposed in literature and full-wave data validate both the accuracy and the effectiveness of the proposed approach.
Substrate Integrated Waveguide (SIW); Artificial Neural Networks
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/1435
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