Blind signal separation on real data: tracking and implementation

Authors:
Paul Baxter;Geoff Spence;John McWhirter
Affiliations:
QinetiQ, Malvern, Worcs, United Kingdom;QinetiQ, Malvern, Worcs, United Kingdom;QinetiQ, Malvern, Worcs, United Kingdom
Venue:
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Year:
2006

Citing 3
Cited 0

An information-maximization approach to blind separation and blind deconvolution

Neural Computation
Kernel Independent Component Analysis

Kernel Independent Component Analysis
Equivariant adaptive source separation

IEEE Transactions on Signal Processing

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Abstract

There are numerous algorithms available for blind signal separation (BSS) of multiple signals, but most of these are optimised for short blocks of data, stationary signals and time invariant mixing matrices. As such, they are unsuitable for real-world applications, which often require tracking BSS carried out in real time with as small a lag as possible. This paper looks at the problems encountered in applying BSS to real data sets and addresses the issue of computationally efficient tracking BSS based on well-understood two-stage block-based approaches. An example is included where the technique is applied to a five-minute section of twin foetal electrocardiogram (ECG) data.