Cluster analysis for EEG biosignal discrimination

O. Georgieva, S. Milanov, P. Georgieva
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引用次数: 3

Abstract

The paper aims to define the ability of unsupervised learning approach to identify emotional biosignals evoked while viewing affected pictures. Two problems are consequently resolved. First, the most important features of the Electroencephalography (EEG) data set have been selected. Secondly, cluster analysis technique is applied in order to extract the specific knowledge of the existing dependencies. The clustering results of particular data subsets are presented and discussed.
脑电生物信号识别的聚类分析
本文旨在定义无监督学习方法识别在观看受影响图片时引起的情绪生物信号的能力。两个问题因此得到解决。首先,选择脑电图(EEG)数据集的最重要特征。其次,利用聚类分析技术提取已有依赖项的具体知识;给出并讨论了特定数据子集的聚类结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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