In underdetermined blind source separation problems, it is common practice to exploit the underlying sparsity of the sources for demixing. In this work, we propose two sparse decom...
It was discovered recently that sparse decomposition by signal dictionaries results in dramatic improvement of the qualities of blind source separation. We exploit sparse decompos...
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
We propose a new approach to underdetermined Blind Source Separation (BSS) using sparse decomposition over monochannel dictionary atoms and compare it to multichannel dictionary a...
In this paper, sparse representation (factorization) of a data matrix is first discussed. An overcomplete basis matrix is estimated by using the K−means method. We have proved ...
Yuanqing Li, Andrzej Cichocki, Shun-ichi Amari, Se...