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A novel approach based on Subspace methods is proposed for extracting the Event Related Potentials (ERPs) from the background Electroencephalograph (EEG) colored noise. First, the enhancement of SNR to the neighborhood of −2 dB is achieved through the ensemble averaging of the EEG data over a limited number of trials. Then a linear estimator is used to reduce further the amount of the EEG signal in...
A “single-trial” signal subspace approach for extracting visual evoked potential (VEP) from the ongoing “colored” electroencephalogram (EEG) noise is proposed. The algorithm applies the generalized eigendecomposition on the covariance matrices of the VEP and noise to transform them jointly into diagonal matrices in order to avoid a pre-whitening stage. The proposed generalized subspace approach (GSA)...
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