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• W1998955224 abstract "A randomized search algorithm for sparse representations of EEG event-related potentials (ERPs) and their statistically independent components is presented. This algorithm combines greedy matching pursuit (MP) technique with covariance matrix adaptation evolution strategy (CMA-ES) to select small number of signal atoms from over-complete wavelet and chirplet dictionaries that offer best approximations of quasi-sparse ERP signals. During the search process, adaptive pruning of signal parameters was used to eliminate redundant or degenerative atoms. As a result, the CMA-ES/MP algorithm is capable of producing accurate efficient and consistent sparse representations of ERP signals and their ICA components. This paper explains the working principles of the algorithm and presents the preliminary results of its use." @default.
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• W1998955224 date "2010-08-01" @default.
• W1998955224 modified "2023-09-23" @default.
• W1998955224 title "Consistent sparse representations of EEG ERP and ICA components based on wavelet and chirplet dictionaries" @default.
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• W1998955224 doi "https://doi.org/10.1109/iembs.2010.5627995" @default.
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