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Inhomogeneous point-process entropy: An instantaneous measure of complexity in discrete systems

Valenza, G and Citi, L and Scilingo, EP and Barbieri, R (2014) 'Inhomogeneous point-process entropy: An instantaneous measure of complexity in discrete systems.' Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 89 (5). ISSN 1539-3755

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Measures of entropy have been widely used to characterize complexity, particularly in physiological dynamical systems modeled in discrete time. Current approaches associate these measures to finite single values within an observation window, thus not being able to characterize the system evolution at each moment in time. Here, we propose a new definition of approximate and sample entropy based on the inhomogeneous point-process theory. The discrete time series is modeled through probability density functions, which characterize and predict the time until the next event occurs as a function of the past history. Laguerre expansions of the Wiener-Volterra autoregressive terms account for the long-term nonlinear information. As the proposed measures of entropy are instantaneously defined through probability functions, the novel indices are able to provide instantaneous tracking of the system complexity. The new measures are tested on synthetic data, as well as on real data gathered from heartbeat dynamics of healthy subjects and patients with cardiac heart failure and gait recordings from short walks of young and elderly subjects. Results show that instantaneous complexity is able to effectively track the system dynamics and is not affected by statistical noise properties. © 2014 American Physical Society.

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Luca Citi
Date Deposited: 23 Jan 2015 13:20
Last Modified: 05 Feb 2019 19:15

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