Title :
Metrics for multivariate power spectra
Author :
Lipeng Ning ; Xianhua Jiang ; Georgiou, Tryphon T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Minnesota, Minneapolis, MN, USA
Abstract :
This paper builds on earlier work in [1] on metrics for power spectral densities (PSD) of multivariable time-series. We present an approach to quantify dissimilarities aimed at optimal prediction and smoothing. Divergence measures are constructed based on the degradation of prediction-error and smoothing-error variances. These induce Riemannian metrics which generalize earlier results for scalar PSD´s.
Keywords :
time series; PSD; Riemannian metrics; divergence measures; multivariable time-series; multivariate power spectra; optimal prediction; power spectral densities; prediction-error variances; smoothing-error variances; Degradation; Geometry; Power measurement; Smoothing methods; Spectral analysis; Technological innovation;
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2012.6426046
