Space-time ICA and EM brain signals
Space-time ICA and EM brain signals
Recently Single Channel ICA has been proposed where it can be shown that the algorithms learn temporal filters for separating the different components. Here we consider the natural extension to learning a set of space-time separating filters. We argue that these are capable of separation above and beyond that possible using only spatial or temporal methods alone. We then consider the potential of these ideas when applied to Ictal Electroencephalographic (EEG) data and Brain Computer Interaction (BCI).
3540744932
577-584
Davies, Mike E.
9ca3625e-5b14-4f1f-90ac-1af468f521ae
James, Christopher C.
a89bec04-f246-48bd-a811-47b4bc20d3d4
Wang, Suogang
36f948bc-4c4e-442c-9052-acdc296c6eb5
2007
Davies, Mike E.
9ca3625e-5b14-4f1f-90ac-1af468f521ae
James, Christopher C.
a89bec04-f246-48bd-a811-47b4bc20d3d4
Wang, Suogang
36f948bc-4c4e-442c-9052-acdc296c6eb5
Davies, Mike E., James, Christopher C. and Wang, Suogang
(2007)
Space-time ICA and EM brain signals.
Davies, Mike E., James, Christopher C., Abdallah, Samer A. and Plumbley, Mark D.
(eds.)
In Independent Component Analysis and Signal Separation: 7th International Conference, ICA 2007, London, UK, September 9-12, 2007, Proceedings.
Springer.
.
(doi:10.1007/978-3-540-74494-8_72).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Recently Single Channel ICA has been proposed where it can be shown that the algorithms learn temporal filters for separating the different components. Here we consider the natural extension to learning a set of space-time separating filters. We argue that these are capable of separation above and beyond that possible using only spatial or temporal methods alone. We then consider the potential of these ideas when applied to Ictal Electroencephalographic (EEG) data and Brain Computer Interaction (BCI).
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Published date: 2007
Venue - Dates:
7th International Conference on Independent Component Analysis and Signal Separation (ICA), London, UK, 2007-09-09 - 2007-09-12
Identifiers
Local EPrints ID: 50456
URI: http://eprints.soton.ac.uk/id/eprint/50456
ISBN: 3540744932
PURE UUID: 5dfb108d-2158-4a0c-adc4-9996317c87bd
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Date deposited: 26 Feb 2008
Last modified: 15 Mar 2024 10:06
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Contributors
Author:
Mike E. Davies
Author:
Christopher C. James
Author:
Suogang Wang
Editor:
Mike E. Davies
Editor:
Christopher C. James
Editor:
Samer A. Abdallah
Editor:
Mark D. Plumbley
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