The fast ICA algorithm with spatial constraints
The fast ICA algorithm with spatial constraints
In many blind source separation (BSS) applications, especially for biomedical signal processing, there are specific expectations regarding the spatial and temporal characteristics of some sources, but post-hoc comparisons between source estimates and anticipated outcomes can be complicated and unreliable. One alternative is to incorporate additional prior knowledge, e.g., about the spatial topography of selected source sensor projections, into the BSS approach by means of constraints. This letter describes a modified version of the FastICA algorithm for spatially constrained BSS, where the estimates of selected columns of the mixing matrix are constrained with reference to predetermined source sensor projections.
biomedical signal processing, fastICA, constrained independent component analysis (cICA), semi-blind source separation (SBSS), spatial constraints
792-795
Hesse, C.W.
53fee7f7-a12e-4783-a426-0d59afbf475d
James, C.J.
b3733b1f-a6a1-4c9b-b75c-6191d4142e52
2005
Hesse, C.W.
53fee7f7-a12e-4783-a426-0d59afbf475d
James, C.J.
b3733b1f-a6a1-4c9b-b75c-6191d4142e52
Hesse, C.W. and James, C.J.
(2005)
The fast ICA algorithm with spatial constraints.
IEEE Signal Processing Letters, 12 (11), .
(doi:10.1109/LSP.2005.856867).
Abstract
In many blind source separation (BSS) applications, especially for biomedical signal processing, there are specific expectations regarding the spatial and temporal characteristics of some sources, but post-hoc comparisons between source estimates and anticipated outcomes can be complicated and unreliable. One alternative is to incorporate additional prior knowledge, e.g., about the spatial topography of selected source sensor projections, into the BSS approach by means of constraints. This letter describes a modified version of the FastICA algorithm for spatially constrained BSS, where the estimates of selected columns of the mixing matrix are constrained with reference to predetermined source sensor projections.
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Published date: 2005
Keywords:
biomedical signal processing, fastICA, constrained independent component analysis (cICA), semi-blind source separation (SBSS), spatial constraints
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Local EPrints ID: 28416
URI: http://eprints.soton.ac.uk/id/eprint/28416
PURE UUID: b0e1feee-afb0-4ca4-98be-12d65909fb17
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Date deposited: 02 May 2006
Last modified: 15 Mar 2024 07:24
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Author:
C.W. Hesse
Author:
C.J. James
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