Numerical validation of a procedure for direct identification of passive linear multiport with convex programming

The paper deals with the numerical validation, performance evaluation and robustness assessment of a procedure for the direct identification of passive transfer matrices based on convex programming. Validation is pursued by producing data sets from lumped multiport systems with random parameters (pa...

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Published in2010 IEEE 14th Workshop on Signal Propagation on Interconnects pp. 141 - 144
Main Authors Chiariello, Andrea G, de Magistris, Massimiliano, De Tommasi, Luciano, Deschrijver, Dirk, Dhaene, Tom
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2010
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Summary:The paper deals with the numerical validation, performance evaluation and robustness assessment of a procedure for the direct identification of passive transfer matrices based on convex programming. Validation is pursued by producing data sets from lumped multiport systems with random parameters (passive, non passive, and possibly affected by random noise), then evaluating the identification ability of the considered method. Results demonstrate how the considered approach satisfactorily covers the passive identification of a large class of data sets, even in presence of significant passivity violations or noise flawed data, at average accuracies comparable with non passive identifications obtained with standard Vector Fitting.
ISBN:9781424476114
1424476119
DOI:10.1109/SPI.2010.5483546