Inferring Phase Equations from Multivariate Time Series

Isao T. Tokuda, Swati Jain, István Z. Kiss, and John L. Hudson
Phys. Rev. Lett. 99, 064101 – Published 8 August 2007

Abstract

An approach is presented for extracting phase equations from multivariate time series data recorded from a network of weakly coupled limit cycle oscillators. Our aim is to estimate important properties of the phase equations including natural frequencies and interaction functions between the oscillators. Our approach requires the measurement of an experimental observable of the oscillators; in contrast with previous methods it does not require measurements in isolated single or two-oscillator setups. This noninvasive technique can be advantageous in biological systems, where extraction of few oscillators may be a difficult task. The method is most efficient when data are taken from the nonsynchronized regime. Applicability to experimental systems is demonstrated by using a network of electrochemical oscillators; the obtained phase model is utilized to predict the synchronization diagram of the system.

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  • Received 5 May 2007

DOI:https://doi.org/10.1103/PhysRevLett.99.064101

©2007 American Physical Society

Authors & Affiliations

Isao T. Tokuda

  • School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, Japan

Swati Jain, István Z. Kiss, and John L. Hudson

  • Department of Chemical Engineering, University of Virginia, 102 Engineers’ Way, Charlottesville, Virginia 22904, USA

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Issue

Vol. 99, Iss. 6 — 10 August 2007

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