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.

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

De Carlo D;
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.
2008
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
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/341218
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