Generalised FastICA for Independent Subspace Analysis
Date
2007
Authors
Shen, Hao
Hueper, Knut
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Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
Independent Subspace Analysis (ISA) was developed as an extension of Independent Component Analysis (ICA) when statistical independences are assumed to exist between groups of components rather than between individual components. Due to the superiority of FastICA against other linear ICA algorithms, an intuitive analogy, the so-called FastISA algorithm, has been proposed to solve the problem of ISA. Experimental evidences so far have shown the capability of FastISA, regardless of any independence criterion. Since standard FastICA can be viewed as a special case of an approximate Newton ICA method and moreover can be generalised as a scalar shifted fixed point algorithm, in this work, we propose two new classes of ISA algorithms, an approximate Newton-like ISA method and a matrix shifted fixed point ISA algorithm on the Graßmann manifold. As an aside, FastISA is a special case in the class of matrix shifted fixed point ISA algorithms. Performances of the proposed algorithms are investigated by numerical experiments.
Description
Keywords
Keywords: Algorithms; Newton-Raphson method; Signal processing; Fast-ICA; Graßmann manifold; Independent Subspace Analysis (ISA); Newton-like method on manifolds; Independent component analysis Fast-ICA; FastISA; Graßmann manifold; Independent Subspace Analysis (ISA); Newton-like method on manifolds
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Source
Proceedings of the 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing
Type
Conference paper
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2037-12-31