KurSL: Model of anharmonic coupled oscillations based on Kuramoto coupling and Sturm-Liouville problem

Journal article


Cadenas, O, Laszuk, D and Slawomir, N (2018). KurSL: Model of anharmonic coupled oscillations based on Kuramoto coupling and Sturm-Liouville problem. Advances in Data Science and Adaptive Analysis. 10 (02).
AuthorsCadenas, O, Laszuk, D and Slawomir, N
Abstract

Physiological signalling is often oscillatory and shows nonlinearity due to complex interactions of underlying processes or signal propagation delays. This is particularly evident in case of brain activity which is subject to various feedback loop interactions between di erent brain structures, that coordinate their activity to support normal function. In order to understand such signalling in health and disease, methods are needed that can deal with such complex oscillatory phenomena. In this paper, a data-driven method for analysing anharmonic oscillations is introduced. The KurSL model incorporates two well-studied components, which in the past have been used separately to analyse oscillatory behaviour. The Sturm-Liouville equations describe a form of a general oscillation, and the Kuramoto coupling model represents a set of oscillators interacting in the phase domain. Integration of these components provides a flexible framework for capturing complex interactions of oscillatory processes of more general form than the most commonly used harmonic oscillators. The paper introduces a mathematical framework of the KurSL model and analyses its behaviour for a variety of parameter ranges. The signi cance of the model follows from its ability to provide information about coupled oscillators' phase dynamics directly from the time series. KurSL o ers a novel framework for analysing a wide range of complex oscillatory behaviours, such as encountered in physiological signals.

KeywordsKuramoto; Sturm-Liouville; Oscillation
Year2018
JournalAdvances in Data Science and Adaptive Analysis
Journal citation10 (02)
PublisherLondon South Bank University
Digital Object Identifier (DOI)doi:https://doi.org/10.1142/S2424922X18400028
Publication dates
Print09 May 2018
Publication process dates
Deposited10 May 2018
Accepted11 Mar 2018
Accepted author manuscript
License
CC BY 4.0
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https://openresearch.lsbu.ac.uk/item/86qyy

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