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Slight parameter changes detection in biological models: a multiresolution approach. (English) Zbl 1021.92001
Summary: This paper deals with the automatic detection of slight parameter changes from the analysis of signals generated by nonlinear biological systems. The interest is focused here on investigating particular aspects of the relation between signal analysis and systems dynamics, involving the automatic detection of changes in parameters of nonlinear systems. The continuous multiresolution entropies combine advantages stemming from both entropy (Shannon and parametric \(q\)-entropy) and wavelet analysis, and have been shown to be sensitive to dynamical complexity changes. Classical statistical approaches offer a new tool that enables the automatic detection of such changes.
In this paper, multiresolution and standard tools for the automatic detection of slight parameter changes in nonlinear dynamical systems from the analysis of the corresponding time series are introduced and compared. The relevance of the multiresolution approach, together with its robustness in the presence of moderate noise, and its comparison is discussed in numerical simulations and applied to biological signals.

92B05 General biology and biomathematics
37N25 Dynamical systems in biology
37M10 Time series analysis of dynamical systems
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