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EEG study on affective valence elicited by novel and familiar pictures using ERD/ERS and SVM-RFE.

, , , , , , and . Medical Biol. Eng. Comput., 52 (2): 149-158 (2014)

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EEG study on affective valence elicited by novel and familiar pictures using ERD/ERS and SVM-RFE., , , , , , and . Medical Biol. Eng. Comput., 52 (2): 149-158 (2014)Application of SVM-RFE on EEG signals for detecting the most relevant scalp regions linked to affective valence processing., , , , , , and . Expert Syst. Appl., 40 (6): 2102-2108 (2013)EEG-based Subject Independent Affective Computing Models., , , , and . INNS Conference on Big Data, volume 53 of Procedia Computer Science, page 375-382. Elsevier, (2015)Mining EEG scalp maps of independent components related to HCT tasks., , , and . EMBC, page 3888-3891. IEEE, (2019)Approach on affective valence detection from EEG signals based on global field power measure and SVM-RFE algorithm., , , , and . IWBBIO, page 163-170. Copicentro Editorial, (2013)Feature Extraction and Classification of Biosignals - Emotion Valence Detection from EEG Signals., , , , , , , and . BIOSIGNALS, page 54-60. SciTePress, (2013)Analysis of eyewitness testimony using electroencephalogram signals., , , and . EMBC, page 894-897. IEEE, (2021)Nonlinear regression metamodels: a systematic approach.. Int. J. Simul. Process. Model., 5 (3): 241-255 (2009)Design Experiments For The Construction Of Simulation Metamodels., and . ECMS, page 338-344. European Council for Modeling and Simulation, (2009)Sequential experimental designs for nonlinear regression metamodels in simulation., and . Simul. Model. Pract. Theory, 16 (9): 1365-1378 (2008)