Sparse multichannel source separation using incoherent K-SVD method
Abolghasemi, V, Ferdowsi, S and Sanei, S (2011) Sparse multichannel source separation using incoherent K-SVD method In: SSP '11, 2011-06-28 - 2011-06-30, Nice, France.
Sparse multichannel source separation using incoherent K-SVD method.pdf
Available under License : See the attached licence file.
In this paper the problem of sparse source separation of linear mixtures is addressed. We propose to apply K-SVD, which is a leading dictionary learning method, for this purpose. Further, a modified gradient-based K-SVD scheme for incoherent dictionary learning and source separation is proposed. The promising results on random synthetic signals reveal the ability of this technique for utilizing in source separation framework. We also suggest BOLD detection fMRI as an application for this method. The preliminary results confirm the successful separation of this type of data.
|Item Type:||Conference or Workshop Item (Conference Paper)|
|Divisions :||Faculty of Engineering and Physical Sciences > Computing Science|
|Identification Number :||https://doi.org/10.1109/SSP.2011.5967736|
|Depositing User :||Symplectic Elements|
|Date Deposited :||14 Jan 2013 10:37|
|Last Modified :||23 Sep 2013 19:56|
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