Abstract:
In this paper, the properties of two recently proposed frequency-domain subspace-based algorithms to estimate discrete-time cross-power spectral density (cross-PSD) and a...Show MoreMetadata
Abstract:
In this paper, the properties of two recently proposed frequency-domain subspace-based algorithms to estimate discrete-time cross-power spectral density (cross-PSD) and auto-power spectral density (auto-PSD) matrices of vector auto-regressive moving-average and moving-average (ARMAMA) models from sampled values of the Welch cross-PSD and auto-PSD estimators on uniform grids of frequencies, are illustrated by numerical and real-life application examples. The latter is concerned with the modeling of acoustic spectra for detecting faults in induction motors.
Published in: 2013 European Control Conference (ECC)
Date of Conference: 17-19 July 2013
Date Added to IEEE Xplore: 02 December 2013
Electronic ISBN:978-3-033-03962-9