Research Abstract


Characterizing global evolutions of complex systems via intermediate network representations

2012年5月25日 Scientific Reports 2 : 423 doi: 10.1038/srep00423


岩山 幸治1,2*、平田 祥人2*、高橋 康介3、渡邊 克巳3、合原 一幸2 & 鈴木 秀幸2

  1. FIRST 合原最先端数理モデルプロジェクト
  2. 東京大学生産技術研究所
  3. 東京大学先端科学技術研究センター
    *岩山 幸治、平田 祥人は、本研究に同等に貢献している。

Recent developments in measurement techniques have enabled us to observe the time series of many components simultaneously. Thus, it is important to understand not only the dynamics of individual time series but also their interactions. Although there are many methods for analysing the interaction between two or more time series, there are very few methods that describe global changes of the interactions over time. Here, we propose an approach to visualise time evolution for the global changes of the interactions in complex systems. This approach consists of two steps. In the first step, we construct a meta-time series of networks. In the second step, we analyse and visualise this meta-time series by using distance and recurrence plots. Our two-step approach involving intermediate network representations elucidates the half-a-day periodicity of foreign exchange markets and a singular functional network in the brain related to perceptual alternations.