Title :
Symmetric tensor decomposition of narrowband single channel signals
Author :
kouchaki, samaneh ; Sanei, Saeid
Author_Institution :
Fac. of Eng. & Phys. Sci., Univ. of Surrey, Guildford, UK
Abstract :
Being able to determine the rank of a symmetric tensor and estimate the number of sources within single channel mixtures are the motives for developing a new approach for decomposition of single channel mixtures. The single channel data is converted to a symmetric tensor and decomposed. As another contribution, the inherent frequency diversity of the time series has been effectively exploited to highlight the subspace of interest. As a useful application, the method has been applied to detect the beta rebound for use in brain computer interfacing.
Keywords :
signal processing; tensors; brain computer interfacing; narrowband single channel signals; single channel mixtures; single channel source separation; symmetric tensor decomposition; Channel estimation; Electroencephalography; Matrix decomposition; Narrowband; Source separation; Tensile stress;
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th
Conference_Location :
A Coruna
DOI :
10.1109/SAM.2014.6882440