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» Data Separation by Sparse Representations
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NIPS
2003
8 years 7 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...
ICIP
2009
IEEE
9 years 7 months ago
Sparsity And Morphological Diversity For Hyperspectral Data Analysis
Recently morphological diversity and sparsity have emerged as new and effective sources of diversity for Blind Source Separation. Based on these new concepts, novel methods such a...
TSP
2016
74views more  TSP 2016»
3 years 2 months ago
Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization
—We propose a sparse coding approach to address the problem of source-sensor localization and speech reconstruction. This approach relies on designing a dictionary of spatialized...
Afsaneh Asaei, Mohammad Javad Taghizadeh, Saeid Ha...
ICONIP
2007
8 years 7 months ago
Flexible Component Analysis for Sparse, Smooth, Nonnegative Coding or Representation
In the paper, we present a new approach to multi-way Blind Source Separation (BSS) and corresponding 3D tensor factorization that has many potential applications in neuroscience an...
Andrzej Cichocki, Anh Huy Phan, Rafal Zdunek, Liqi...
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