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Riemannian Distances for Signal Classification by...
Journal article

Riemannian Distances for Signal Classification by Power Spectral Density

Abstract

Signal classification is an important issue in many branches of science and engineering. In signal classification, a feature of the signals is often selected for similarity comparison. A distance metric must then be established to measure the dissimilarities between different signal features. Due to the natural characteristics of dynamic systems, the power spectral density (PSD) of a signal is often used as a feature to facilitate …

Authors

Li Y; Wong KM

Journal

IEEE Journal of Selected Topics in Signal Processing, Vol. 7, No. 4, pp. 655–669

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

August 1, 2013

DOI

10.1109/jstsp.2013.2260320

ISSN

1932-4553