A classification procedure based on timefrequency decomposition of the signal is presented. Parametric spectral ESPRIT method is used for estimation of relevant parameters of signal components and specific areas of the time-frequency plane are chosen, where the signal is expected to show most characteristic patterns. Classification is based on timedomain correlation of reconstructed signals. It is applied to event classification of non-stationary electric signals obtained from a simulated power converter.
Z., L., Leccese, F. (2010). Classification of Electric Signals Based on Time–Frequency Signal Decomposition. In IWSSIP 2010 - 17th International Conference on Systems, Signals and Image Processing.
Classification of Electric Signals Based on Time–Frequency Signal Decomposition
LECCESE, Fabio
2010-01-01
Abstract
A classification procedure based on timefrequency decomposition of the signal is presented. Parametric spectral ESPRIT method is used for estimation of relevant parameters of signal components and specific areas of the time-frequency plane are chosen, where the signal is expected to show most characteristic patterns. Classification is based on timedomain correlation of reconstructed signals. It is applied to event classification of non-stationary electric signals obtained from a simulated power converter.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
