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NIPS
2003
13 years 9 months ago
Sparse Representation and Its Applications in Blind Source Separation
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...
TNN
2008
122views more  TNN 2008»
13 years 7 months ago
Two-Microphone Separation of Speech Mixtures
Separation of speech mixtures, often referred to as the cocktail party problem, has been studied for decades. In many source separation tasks, the separation method is limited by t...
Michael Syskind Pedersen, DeLiang Wang, Jan Larsen...
IJCNN
2000
IEEE
14 years 3 days ago
ICA for Noisy Neurobiological Data
ICA (Independent Component Analysis) is a new technique for analyzing multi-variant data. Lots of results are reported in the field of neurobiological data analysis such as EEG (...
Shiro Ikeda, Keisuke Toyama
ISMIR
2005
Springer
215views Music» more  ISMIR 2005»
14 years 1 months ago
Separation of Vocals from Polyphonic Audio Recordings
Source separation techniques like independent component analysis and the more recent non-negative matrix factorization are gaining widespread use for the monaural separation of in...
Shankar Vembu, Stephan Baumann
ICPR
2008
IEEE
14 years 2 months ago
Illuminant dependence of PCA, NMF and NTF in spectral color imaging
In this study Principal Component Analysis (PCA), Non-negative Matrix Factorization (NMF) and Nonnegative Tensor Factorization (NTF) are applied as dimension reduction methods in ...
Alexey Andriyashin, Jussi Parkkinen, Timo Jaaskela...