A new methodology for in-situ calibration of a neural network-based software sensor for S-parameter prediction in six-port reflectometers
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URI: http://hdl.handle.net/10317/1473Share
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Electromagnetismo y MateriaKnowledge Area
Teoría de la Señal y las ComunicacionesPublication date
2006Publisher
Elsevier ScienceBibliographic Citation
PEDREÑO MOLINA, J.L., PINZOLAS PRADO, M., MONZÓ CABRERA, J. A new methodology for in-situ calibration of a neural network-based software sensor for S-parameter prediction in six-port reflectometers. Neurocomputing, Vol. 69 : 2451-2455, 2006. ISSN 0925-2312Peer review
SíKeywords
Six-port reflectometerS-parameter prediction
Six_port calibration
Neural Networks
Microwave cavity measurement
Abstract
In this work, a neural network-based software sensor is proposed for determining the reflection coefficient from measurements
obtained by a six-port reflectometer. The proposed software sensor is able to cope with the nonlinearities and noise inherent to the
measurement electronics, without needing additional calibration. To extract data for the calibration, a new method that allows in situ
calibration is applied. Experimental evidence of the feasibility of the proposed method is given using a simulation testbench.
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