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Communication Dans Un Congrès Année : 2010

Common SpatioTemporal Pattern Analysis

Nisrine Jrad
Bertrand Rivet
Marco Congedo

Résumé

In this work we present a method for the estimation of a rank-one pattern living in two heterogeneous spaces, when observed through a mixture in multiple observation sets. Using a well chosen representation for an observed set of second order tensors (matrices), a singular value decomposition of the set structure yields an accurate es- timate under some widely acceptable conditions. The method performs a completely algebraic estimation in both heterogeneous spaces without the need for heuristic parameters. Contrary to existing methods, neither independence in one of the spaces, nor joint decorrelation in both of the heterogeneous spaces is required. In addition, because the method is not variance based in the input space, it has the critical advantage of being applicable with low signal-to-noise ratios. This makes this method an excellent candidate ,e.g., for the direct estimation of the spatio-temporal P300 pattern in passive exogenous brain computer interface paradigms. For these applications it is often sufficient to consider quasi-decorrelation in the temporal space only, while we do not want to impose a similar con- straint in the spatial domain.
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Dates et versions

hal-00524884 , version 1 (09-10-2010)

Identifiants

Citer

Ronald Phlypo, Nisrine Jrad, Bertrand Rivet, Marco Congedo. Common SpatioTemporal Pattern Analysis. LVA/ICA 2010 - 9th International Conference on Latent Variable Analysis and Signal Separation, Sep 2010, Saint Malo, France. pp.596--603, ⟨10.1007/978-3-642-15995-4_74⟩. ⟨hal-00524884⟩
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