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|Title: ||Estimating the distribution of dynamic invariants: illustrated with an application to human photo-plethysmographic time series|
|Authors: ||Small, Michael|
|Issue Date: ||23-Jul-2007 |
|Publisher: ||BioMed Central Ltd.|
|Citation: ||Nonlinear biomedical physics, 23 July 2007, v. 1, 8, p. 1-11.|
|Abstract: ||Dynamic invariants are often estimated from experimental time series with the aim of
differentiating between different physical states in the underlying system. The most popular schemes for estimating dynamic invariants are capable of estimating confidence intervals, however, such confidence intervals do not reflect variability in the underlying dynamics. We propose a surrogate based method to estimate the expected distribution of values under the null hypothesis that the underlying deterministic dynamics are stationary. We demonstrate the application of this method by considering four recordings of human pulse waveforms in differing physiological states and show that correlation dimension and entropy are insufficient to differentiate between these states. In contrast, algorithmic complexity can clearly differentiate between all four rhythms.|
|Description: ||DOI: 10.1186/1753-4631-1-8|
|Rights: ||© 2007 Small; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.|
|Type: ||Journal/Magazine Article|
|Appears in Collections:||EIE Journal/Magazine Articles|
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