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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)

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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)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)Spectral turbulence measuring as feature extraction method from EEG on affective computing., , , , and . Biomed. Signal Process. Control., 8 (6): 945-950 (2013)Learning to decode human emotions from event-related potentials., , , , , and . Neural Comput. Appl., 26 (3): 573-580 (2015)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)Feature Extraction and Classification of Biosignals - Emotion Valence Detection from EEG Signals., , , , , , , and . BIOSIGNALS, page 54-60. SciTePress, (2013)Reproduction-related cognitive processing and distress among young adult women: the role of personal breast cancer history., , , , and . Cogn. Process., 22 (3): 569-578 (2021)Analysis of eyewitness testimony using electroencephalogram signals., , , and . EMBC, page 894-897. IEEE, (2021)