文章詳目資料

International Journal of Applied Science and Engineering Scopus

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篇名 Categorization of Alpha Wave Music by SOM Reduction
卷期 16:2
作者 Yu-Lung LoYi-Lan Deng
頁次 095-107
關鍵字 Music classificationalpha wave musicartificial neural networkScopus
出刊日期 201909
DOI 10.6703/IJASE.201909_16(2).095

中文摘要

英文摘要

People usually listen music to refresh, relax and help sleep. While humans are in various states of minds, there are different frequencies of brain waves detected. Some music can resonate with human brain waves to achieve the better effect on someone's state of mind. Among brain waves, the alpha wave predominantly appears when people are in wakeful relaxation with closed eyes. There has been several medical reports demonstrated that some specific music, called alpha wave music, can resonate with the alpha wave and strengthen it. Therefore, when people take the rest and listen to the alpha wave music at the same time, it can be very helpful to achieve better relaxing. However, the alpha wave music album is not popular on the market because it only can be classified manually by expertise. Until now, there is still very little research on the automatic identification of alpha wave music. This study analyses the music characterizations and tries to categorize the alpha wave music by Self Organizing Map (SOM) reduction.

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