Link of Data Synchronization to Self-Organizing Map Algorithm
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概要
- 論文の詳細を見る
We have recently developed a method for feature extraction from multivariate data using an analogue of Kuramotos dynamics for modeling collective synchronization in a network of coupled phase oscillators. In our method, which we call data synchronization, phase oscillators carrying multivariate data in their natural and updated rhythms achieve partial synchronizations. Their common rhythms are interpreted as the template vectors representing the general features of the data set. In this study, we discuss the link of data synchronization to the self-organizing map algorithm as a popular method for data mining and show through numerical experiments how our method can overcome the disadvantages of the self-organizing map algorithm in that unintentional selections of inappropriate reference vectors lead to false feature patterns.
- （社）電子情報通信学会の論文
- 2009-01-01
著者
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MIYANO Takaya
Department of Micro System Technology, Ritsumeikan University
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TSUTSUI Takako
Department of Health and Social Services, National Institute of Public Health
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Tsutsui Takako
Department Of Health And Social Services National Institute Of Public Health
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Miyano Takaya
Department Of Micro System Technology Ritsumeikan University
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