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A filtering approach to underdetermined blind source separation with application to temporomandibular disorders

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conference contribution
posted on 2009-12-02, 12:35 authored by Clive Cheong Took, Saeid Sanei, Jonathon Chambers
This paper addresses the underdetermined blind source separation problem, using a filtering approach. We have developed an extension of the FastICA algorithm which exploits the disparity in the kurtoses of the underlying sources to estimate the mixing matrix and thereafter the recovery of the sources is achieved by employing the l1-norm algorithm. Also, we demonstrate how promising FastICA can be to extract the sources, without utilizing the l1-norm algorithm. Furthermore, we illustrate how this scenario is particularly suitable to the separation of the temporomandibular joint (TMJ) sounds, crucial in the diagnosis of temporomandibular disorders (TMDs)

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

TOOK, C.C., SANEI, S. and CHAMBERS, J., 2006. A filtering approach to underdetermined blind source separation with application to temporomandibular disorders. IN: Proceedings of the 2006 IEEE Conference on Acoustics, Speech and Signal Processing. ICASSP 2006, Toulouse, 14-19 May 2006, Vol 3

Publisher

© IEEE

Version

  • VoR (Version of Record)

Publication date

2006

Notes

This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISBN

142440469X

ISSN

1520-6149

Language

  • en

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