TY - GEN
T1 - Adaptive sparse factorization for even-determined and over-determined blind source separation
AU - Wang, Fuxiang
AU - Zhang, Jun
PY - 2009
Y1 - 2009
N2 - In this paper, we present an adaptive sparse factorization method for even-determined and over-determined blind source separation, where the sources are assumed to be sparse. The objective of our method is to find a demixing matrix to make the output signal as sparse as possible. First, a cost function measuring the sparsity of the output signals is introduced. Then an adaptive algorithm for the learning of the demixing matrix is proposed by the nature gradient. Compared to Independent Component Analysis, the new method can deal with the mixing cases that the sources are mutually correlated. Simulation results show the effectiveness of the new method.
AB - In this paper, we present an adaptive sparse factorization method for even-determined and over-determined blind source separation, where the sources are assumed to be sparse. The objective of our method is to find a demixing matrix to make the output signal as sparse as possible. First, a cost function measuring the sparsity of the output signals is introduced. Then an adaptive algorithm for the learning of the demixing matrix is proposed by the nature gradient. Compared to Independent Component Analysis, the new method can deal with the mixing cases that the sources are mutually correlated. Simulation results show the effectiveness of the new method.
KW - Blind source separation
KW - Independent component analysis
KW - Penalty function
KW - Sparse representation
UR - https://www.scopus.com/pages/publications/77949705080
U2 - 10.1109/CISE.2009.5366379
DO - 10.1109/CISE.2009.5366379
M3 - Conference contribution
AN - SCOPUS:77949705080
SN - 9781424445073
T3 - Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
BT - Proceedings - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
T2 - 2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009
Y2 - 11 December 2009 through 13 December 2009
ER -