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The inverse approach to chronotaxic systems for single-variable time series

Research output: Contribution to journalJournal article


Article number032904
Journal publication date10/03/2014
JournalPhysical Review E
Number of pages13
Original languageEnglish


Following the development of a new class of self-sustained oscillators with a time-varying but stable frequency, the inverse approach to these systems is now formulated. We show how observed data arranged in a single-variable time series can be used to recognise such systems. This approach makes use of time-frequency domain information using the wavelet transform as well as the recently-developed method of Bayesian-based inference. In addition, a new set of methods, named phase fluctuation analysis, is introduced to detect the defining properties of the new class of systems by directly analysing the statistics of the observed perturbations. We apply these methods to numerical examples but also elaborate further on the cardiac system.

Bibliographic note

Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.