ICA 2007

ICA 2007
7th International Conference on
Independent Component Analysis
and Signal Separation

London, UK        9 - 12 September 2007

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Paper No: 64

Estimating the mixing matrix in Sparse Component Analysis based on converting a multiple dominant to a single dominant problem

Author(s): Nima Noorshams, Babaie-Zadeh Massoud, Christian Jutten

Abstract

We propose a new method for estimating the mixing matrix, A, in the linear model x(t)=A s(t), t=1,...,T$, for the problem of underdetermined Sparse Component Analysis (SCA). Contrary to most previous algorithms, there can be more than one dominant source at each instant (we call it a ``multiple dominant'' problem). The main idea is to convert the multiple dominant problem to a series of single dominant problems, which may be solved by well-known methods. Each of these single dominant problems results in the determination of some columns of A. This results in a huge decrease in computations, which lets us to solve higher dimension problems that were not possible before.

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