title: Inference of time-evolving coupled dynamical systems in the presence of noise.
abstract: A new method is introduced for analysis of interactions between time-dependent coupled oscillators, based on the signals they generate. It distinguishes unsynchronized dynamics from noise-induced phase slips and enables the evolution of the coupling functions and other parameters to be followed. It is based on phase dynamics, with Bayesian inference of the time-evolving parameters achieved by shaping the prior densities to incorporate knowledge of previous samples. The method is tested numerically and applied to reveal and quantify the time-varying nature of cardiorespiratory interactions.
authors.affiliation: Department of Physics, Lancaster University, Lancaster, LA1 4YB, United Kingdom.
authors.forename: Tomislav
authors.initials: T
authors.lastname: Stankovski
authors.forename: Andrea
authors.initials: A
authors.lastname: Duggento
authors.forename: Peter V E
authors.initials: PV
authors.lastname: McClintock
authors.forename: Aneta
authors.initials: A
authors.lastname: Stefanovska
mesh_terms: D005583:Fourier Analysis; D008962:Models, Theoretical; D009991:Oscillometry; D010507:Periodicity; D059629:Signal-To-Noise Ratio