Symmetric Tensor Decomposition of Narrowband Single Channel Signals

Samaneh Kouchaki; Saeid Sanei; IEEE

doi:10.1109/SAM.2014.6882440

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Conference proceeding

Symmetric Tensor Decomposition of Narrowband Single Channel Signals

Samaneh Kouchaki, Saeid Sanei and IEEE

2014 IEEE 8TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM), pp.453-456

Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop

01/01/2014

DOI: https://doi.org/10.1109/SAM.2014.6882440

Abstract

Engineering

Engineering, Electrical & Electronic

Science & Technology

Technology

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.

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Title: Symmetric Tensor Decomposition of Narrowband Single Channel Signals
Creators: Samaneh Kouchaki - University of Surrey
Saeid Sanei - University of Surrey
IEEE
Publication Details: 2014 IEEE 8TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM), pp.453-456
Series: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
Publisher: IEEE
Number of pages: 4
Date published: 01/01/2014
Identifiers: 99783064502346
Academic Unit: School of Computer Science and Electronic Engineering
Language: English
Resource Type: Conference proceeding

Symmetric Tensor Decomposition of Narrowband Single Channel Signals

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