Change-point detection with recurrence networks
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概要
- 論文の詳細を見る
Change-point detection based on an observed time series has emerged as an important method for detecting changes in dynamics of real-world systems. Recently, recurrence networks have been shown to be useful, which are network representations of recurrences, to analyze underlying dynamics. In this paper, we propose a new method for detecting dynamical changes using recurrence networks. The proposed method extracts a group of time indices that share the same dynamics as a community of the recurrence network. In addition, some numerical simulations are presented to verify the validity of this method.
- The Institute of Electronics, Information and Communication Engineersの論文
著者
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Aihara Kazuyuki
Institute Of Industrial Science The University Of Tokyo
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Hirata Yoshito
Institute Of Industrial Science The University Of Tokyo
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Iwayama Koji
FIRST, Aihara Innovative Mathematical Modelling Project, JST
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Suzuki Hideyuki
Institute of Industrial Science, The University of Tokyo
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