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Support vector regression machines to evaluate resonant frequencies of elliptic substrate integrated waveguide resonators

Academic Article
Publication Date:
2008
abstract:
In this paper an efficient technique for the determination of the resonances of elliptic Substrate Integrated Waveguide (SIW) resonators is presented. The method is based on the implementation of Support Vector Regression Machines trained using a fast algorithm for the computation of the resonant frequencies of SIW structures. Results for resonators with a wide range of parameters will be presented. A comparison with results obtained with Multi Layer Perceptron Artificial Neural Network and with full wave simulations will show the effectiveness of the proposed approach.
Iris type:
01.01 Articolo in rivista
Keywords:
Neural networks; Substrate integrated waveguides; Substrate-integrated waveguide; Support vector regression; Artificial Neural Network; Fast algorithms; Full-wave simulations; Multi-Layer Perceptron; Resonant frequencies; Food processing; Microwave circuits; Natural frequencies; Resonators; Vectors; Waveguides
List of contributors:
DE CARLO, Domenico
Handle:
https://iris.cnr.it/handle/20.500.14243/341218
Published in:
ELECTROMAGNETIC WAVES (CAMB. MASS.)
Journal
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http://www.scopus.com/record/display.url?eid=2-s2.0-49549119388&origin=inward
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