A modified underdetermined blind source separation algorithm.pdf (334.75 kB)
A modified underdetermined blind source separation algorithm using competitive learning
conference contribution
posted on 2010-02-04, 17:27 authored by Yuhui Luo, Jonathon ChambersThe problem of underdetermined blind source separation
is addressed. An advanced classification method
based upon competitive learning is proposed for automatically
determining the number of active sources
over the observation. Its introduction in underdetermined
blind source separation successfully overcomes
the drawback of an existing method, in which the goal
of separating more sources than the number of available
mixtures is achieved by exploiting the sparsity of
the non-stationary sources in the time-frequency domain.
Simulation studies are presented to support the
proposed approach.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Citation
LUO, Y. and CHAMBERS, J.A., 2003. A modified underdetermined blind source separation algorithm using competitive learning. IN: Proceedings of 2003 3rd International Symposium on Image and Signal Processing and Analysis (ISPA 2003), Rome, Italy, 18-20 September, Vol. 2, pp. 966-969.Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
2003Notes
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
953-184-061-XISSN
1330-1012Language
- en