Geometrical invariability of transformation between a time series and a complex network

Yi Zhao, Tongfeng Weng, Shengkui Ye

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)

Abstract

We present a dynamically equivalent transformation between time series and complex networks based on coarse geometry theory. In terms of quasi-isometric maps, we characterize how the underlying geometrical characters of complex systems are preserved during transformations. Fractal dimensions are shown to be the same for time series (or complex network) and its transformed counterpart. Results from the Rössler system, fractional Brownian motion, synthetic networks, and real networks support our findings. This work gives theoretical evidences for an equivalent transformation between time series and networks.

Original languageEnglish
Article number012804
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume90
Issue number1
DOIs
Publication statusPublished - 9 Jul 2014

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