Inference of a nonlinear stochastic model of the cardiorespiratory interaction

Abstract

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

5 pages, 4 figures, 1 table. accepted for publication in Phys. Rev. Lett. 2005

References in corpus (2)

• Helioseismology
• Better Nonlinear Models from Noisy Data: Attractors with Maximum Likelihood

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