Lancaster EPrints

Inference of a nonlinear stochastic model of the cardiorespiratory interaction.

Stefanovska, Aneta and Luchinsky, D. G. and McClintock, Peter V. E. and Smelyanskiy, V. N. (2005) Inference of a nonlinear stochastic model of the cardiorespiratory interaction. Physical Review Letters, 94 (9). 098101.

[img]
Preview
PDF (PRL2005Inference.pdf) - Published Version
Download (898Kb) | Preview

    Abstract

    We reconstruct a nonlinear stochastic model of the cardiorespiratory interaction in terms of a set of polynomial basis functions representing the nonlinear force governing system oscillations. The strength and direction of coupling and noise intensity are simultaneously inferred from a univariate blood pressure signal. Our new inference technique does not require extensive global optimization, and it is applicable to a wide range of complex dynamical systems subject to noise.

    Item Type: Article
    Journal or Publication Title: Physical Review Letters
    Additional Information: First use of Bayesian inference to build a nonlinear stochastic model of the cardio-respiratory interaction in terms of polynomial basis functions, directly from a univariate blood pressure signal. The technique is widely applicable in dynamical modelling. RAE_import_type : Journal article RAE_uoa_type : Physics
    Subjects: Q Science > QC Physics
    Departments: Faculty of Science and Technology > Physics
    ID Code: 2281
    Deposited By: ep_importer
    Deposited On: 04 Apr 2008 09:03
    Refereed?: Yes
    Published?: Published
    Last Modified: 14 Apr 2015 09:22
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/2281

    Actions (login required)

    View Item