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ICASSP
2009
IEEE
14 years 9 months ago
Blind sparse source separation for unknown number of sources using Gaussian mixture model fitting with Dirichlet prior
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 ...
Shoko Araki, Tomohiro Nakatani, Hiroshi Sawada, Sh...
ICML
2008
IEEE
16 years 20 days ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann
ICA
2010
Springer
15 years 29 days ago
Blind Source Separation Based on Time-Frequency Sparseness in the Presence of Spatial Aliasing
In this paper, we propose a novel method for blind source separation (BSS) based on time-frequency sparseness (TF) that can estimate the number of sources and time-frequency masks,...
Benedikt Loesch, Bin Yang
MICCAI
2009
Springer
16 years 1 months ago
Functional Segmentation of fMRI Data Using Adaptive Non-negative Sparse PCA (ANSPCA)
We propose a novel method for functional segmentation of fMRI data that incorporates multiple functional attributes such as activation effects and functional connectivity, under a ...
Bernard Ng, Rafeef Abugharbieh, Martin J. McKeow...
ICONIP
2007
15 years 1 months ago
Sparse Super Symmetric Tensor Factorization
In the paper we derive and discuss a wide class of algorithms for 3D Super-symmetric nonnegative Tensor Factorization (SNTF) or nonnegative symmetric PARAFAC, and as a special case...
Andrzej Cichocki, Marko Jankovic, Rafal Zdunek, Sh...