BCI competition 2003-data sets Ib and IIb: feature extraction from event-related brain potentials with the continuous wavelet transform and the t-value scalogram

By Vladimir Bostanov. IEEE Transactions on Biomedical Engineering, 2004

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BCI competition 2003-data set IIb: support vector machines for the P300 speller paradigm (2004, background): “First experiments with continuous wavelets [9] have been promising.”
Toward enhanced P300 speller performance. (2008, neutral): “, 2000; Sellers and Donchin, 2006), wavelets (Bostanov, 2004), support vector machines (Kaper et al.”
A comparison of classification techniques for the P300 Speller (2006, methodology): “Several classification techniques have demonstrated notable performance for the P300 Speller, including stepwise linear discriminant analysis [2, 5], support vector machines [8, 10, 11], wavelets [1] and matched filtering [14].”
Brain Computer Interfaces, a Review (2012, methodology): “The Mexican Hat wavelet is well localized in the time domain and is employed for the localization of ERP components in time [179].”