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1 Journal article

Convolutive ICA for Spatio-Temporal Analysis of EEG

Dyrholm, Mads; Makeig, Scott; Hansen, Lars Kai

Neural Computation — 2007, Volume 19, pp. 934-955

in the convolutive model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving an EEG ICA subspace. Initial results suggest that in some cases convolutive mixing may be a more realistic model for EEG signals than the instantaneous ICA model.

Year: 2007

Language: English

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2 Journal article

Model selection for convolutive ICA with an application to spatiotemporal analysis of EEG

Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

Neural Computation — 2007, Volume 19, Issue 4, pp. 934-955

We present a new algorithm for maximum likelihood convolutive independent component analysis (ICA) in which components are unmixed using stable autoregressive filters determined implicitly by estimating a convolutive model of the mixing process. By introducing a convolutive mixing model

Year: 2007

Language: English

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