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IJON
2002
128views more  IJON 2002»
13 years 4 months ago
Extraction of a source from multichannel data using sparse decomposition
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...
Michael Zibulevsky, Yehoshua Y. Zeevi
ICASSP
2011
IEEE
12 years 8 months ago
Sparse common spatial patterns in brain computer interface applications
The Common Spatial Pattern (CSP) method is a powerful technique for feature extraction from multichannel neural activity and widely used in brain computer interface (BCI) applicat...
Fikri Goksu, Nuri Firat Ince, Ahmed H. Tewfik
ICASSP
2009
IEEE
13 years 8 months ago
Multichannel nonnegative matrix factorization in convolutive mixtures. With application to blind audio source separation
We consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly underdetermined convolutive mixture of source signals...
Alexey Ozerov, Cédric Févotte
TSP
2010
12 years 11 months ago
A deflation procedure for subspace decomposition
A general deflation framework is described for the separation of a desired signal subspace of arbitrary dimensions from noisy multichannel observations. The method simultaneously u...
Reza Sameni, Christian Jutten, Mohammad Bagher Sha...
PKDD
2007
Springer
143views Data Mining» more  PKDD 2007»
13 years 10 months ago
Using the Web to Reduce Data Sparseness in Pattern-Based Information Extraction
Textual patterns have been used effectively to extract information from large text collections. However they rely heavily on textual redundancy in the sense that facts have to be m...
Sebastian Blohm, Philipp Cimiano