首页> 外文期刊>International Journal of Knowledge-Based in Intelligent Engineering Systems >A learning based self-organized additive fuzzy clustering method and its application for EEG data
【24h】

A learning based self-organized additive fuzzy clustering method and its application for EEG data

机译:基于学习的自组织加法模糊聚类方法及其在脑电数据中的应用

获取原文
获取原文并翻译 | 示例
           

摘要

In this paper, a learning based fuzzy clustering method and its application to a set of electroencephalogram (EEG) data is given. The proposed method combines the learning process of noise to a conventional self-organized additive fuzzy clustering method. This is done by using the inner product of a pair of degrees of belongingness of objects. By learning the status of the noise in each iteration of the algorithm, the proposed method can obtain a more adaptable result.
机译:本文提出了一种基于学习的模糊聚类方法,并将其应用于脑电图数据集。该方法将噪声的学习过程与传统的自组织加法模糊聚类方法相结合。这是通过使用对象的一对关联度的内积来完成的。通过学习算法每次迭代中的噪声状态,所提出的方法可以获得更加自适应的结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号