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: 103

Shifted Independent Component Analysis

Author(s): Morten Mørup, Kristoffer H. Madsen, Lars K. Hansen

Abstract

Delayed mixing is a problem of theoretical interest and practical importance, e.g., in speech processing, bio-medical signal analysis and financial data modelling. Most previous analyses have been based on models with integer shifts, i.e., shifts by a number of samples, and have often been carried out using time-domain representation. Here, we explore the fact that a shift t in the time domain corresponds to a multiplication of exp(-iwt) in the frequency domain. Using this property an algorithm in the case of sources<=sensors allowing arbitrary mixing and delays is developed. The algorithm is based on the following steps: 1) Find a subspace of shifted sources. 2) Resolve shift and rotation ambiguity by information maximization in the complex domain. The algorithm is proven to correctly identify the components of synthetic data. However, the problem is prune to local minima and difficulties arise especially in the presence of large delays and high frequency sources. A Matlab implementation can be downloaded from www2.imm.dtu.dk/pubdb/views/publication_details.php? id=5206.

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