Towards a Protocol for Adaptive Dynamical Bayesian Inference: Case of Limit-Cycle Oscillators
Journal
Journal of Electrical Engineering and Information Technologies
Date Issued
2020-12-14
Author(s)
DOI
534.322.3.015:57.08]:519.226
Abstract
Several methods exist that allow the study of the interactions between dynamic systems in nature. Among them is the method of dynamic Bayesian inference, which allows reconstruction of a model that describes the interactions between different dynamical systems, based on the measured time series originating from these systems. Based on an investigation of a known system of two coupled phase oscillators, an algorithm for improving this method has been proposed, by adaptively determining two parameters that were previously arbitrarily selected – the time win-dow and the propagation parameter. This paper presents the results of the evaluation of the introduced algorithm on a second system of coupled oscillators - limit-cycle Poincaré oscillators in the presence of noise. The performed analysis confirmed the relevance of the proposed algorithm for improved model inference, which allows for a deeper understanding of the interactions described by the coupling functions of the dynamical systems.
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