In recent years, Artificial Neural networks (ANNs) have been intensively employed to build smart model of microwave devices. In this paper a characterization of lossy SIW resonators by means of Multilayer Perceptron Neural Networks (MLPNNs) on Graphics Processing Unit (GPU), is presented. Once properly selected and trained, a MLPNN can evaluate the lossy SIW resonator's resonant frequency fr and the pertaining quality factor Q at a shorter time than the full-wave rigorous model. In this way, fast parametric models of SIWstructures to employ for the design and optimization of microwave devices, exploiting the computational power of GPUs, can be obtained.

Characterization of lossy SIW resonators based on multilayer perceptron neural networks on graphics processing unit,

ANGIULLI, Giovanni;
2013

Abstract

In recent years, Artificial Neural networks (ANNs) have been intensively employed to build smart model of microwave devices. In this paper a characterization of lossy SIW resonators by means of Multilayer Perceptron Neural Networks (MLPNNs) on Graphics Processing Unit (GPU), is presented. Once properly selected and trained, a MLPNN can evaluate the lossy SIW resonator's resonant frequency fr and the pertaining quality factor Q at a shorter time than the full-wave rigorous model. In this way, fast parametric models of SIWstructures to employ for the design and optimization of microwave devices, exploiting the computational power of GPUs, can be obtained.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/6420
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