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Multidimensional independent subspace analysis by natural gradient

100%

Wang F. , Zhang L. , Li R. , Zhou Y. , Liu N.

tom R. 88, nr 9b

51-54

Multidimensional Independent Subspace Analysis (MISA) as an extended Independent Component Analysis (ICA) method has been considered. The general and detailed definition, existence, uniqueness, separability of the MISA model are given and the relationships between ICA and MISA are also discussed. The natural gradient separation algorithm and corresponding simulation results for MISA are constructed based on the maximum likelihood theory and natural gradient method.

W artykule zaprezentowano metodę MISA – multidimensional independent subspace analysis. Przedstawiono też metode IOCA – independent component analysis. Opracowano algorytm separacji – natural gradient separation algorithm.

A comparison of algorithms for separation of synchronous subspaces

84%

Almeida M. , Bioucas-Dias J. , Vigário R. , Oja E.

tom Vol. 60, nr 3

455-460

Independent Subspace Analysis (ISA) consists in separating sets (subspaces) of dependent sources, with different sets being independent of each other. While a few algorithms have been proposed to solve this problem, they are all completely general in the sense that they do not make any assumptions on the intra-subspace dependency. In this paper, we address the ISA problem in the specific context of Separation of Synchronous Sources (SSS), i.e., we aim to solve the ISA problem when the intra-subspace dependency is known to be perfect phase synchrony between all sources in that subspace. We compare multiple algorithmic solutions for this problem, by analyzing their performance on an MEG-like dataset.