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A study on the analysis of auditory cortex active status by music genre: Drawing on EEG

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dc.contributor.authorPark, S.-M.-
dc.contributor.authorSim, K.-B.-
dc.date.accessioned2021-09-16T06:40:53Z-
dc.date.available2021-09-16T06:40:53Z-
dc.date.issued2011-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/49254-
dc.description.abstractMusic is the pattern of sounds produced by people singing of playing instruments. Thus, the music is made by people. Music composer, will be planted in the human emotions, put the listener is able to feel a similar sentiment. Especially, interesting from our point of view is that music analysis, the emotions of the people can be analyzed. This paper focuses on the analysis of auditory cortex active status by music genre. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP(Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG. In addition, drawing on LORETA(Low Resolution Brain Electromagnetic Tomography)program have attempt to design location of electrode in brain. And finally, using EEGLAB, the relationship of music and the auditory cortex active status could be concluded. © 2011 IEEE.-
dc.format.extent4-
dc.language영어-
dc.language.isoENG-
dc.titleA study on the analysis of auditory cortex active status by music genre: Drawing on EEG-
dc.typeArticle-
dc.identifier.doi10.1109/FSKD.2011.6019916-
dc.identifier.bibliographicCitationProceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, v.3, pp 1916 - 1919-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-80053414825-
dc.citation.endPage1919-
dc.citation.startPage1916-
dc.citation.titleProceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011-
dc.citation.volume3-
dc.type.docTypeConference Paper-
dc.subject.keywordAuthorBrain-Computer Interface-
dc.subject.keywordAuthorEEG-
dc.subject.keywordAuthorMusic Genre Distinction-
dc.subject.keywordAuthorPattern Recognition-
dc.subject.keywordAuthorVariance-Considered Machine-
dc.subject.keywordPlusAuditory cortex-
dc.subject.keywordPlusAveraging method-
dc.subject.keywordPlusEEG signals-
dc.subject.keywordPlusEvent related potentials-
dc.subject.keywordPlusHuman emotion-
dc.subject.keywordPlusICA algorithms-
dc.subject.keywordPlusLow resolution brain electromagnetic tomographies-
dc.subject.keywordPlusMusic analysis-
dc.subject.keywordPlusMusic composers-
dc.subject.keywordPlusMusic genre-
dc.subject.keywordPlusNoise removal-
dc.subject.keywordPlusVariance-Considered Machine-
dc.subject.keywordPlusFuzzy systems-
dc.subject.keywordPlusPattern recognition-
dc.subject.keywordPlusInterfaces (computer)-
dc.description.journalRegisteredClassscopus-
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