Deconvolution is a classic problem in many disciplines of engineering and science and frequently faced also in the study of physiological and pharmacokinetic systems. In this chapter, we first introduce the deconvolution problem for physiological systems and its inherent difficulties in a formal manner. Then, we present a detailed description of the regularization method, a classic nonparametric approach which has some significant advantages over other techniques, especially if it is embedded in a stochastic setting. Finally, other deconvolution methods, both parametric and nonparametric, are briefly reviewed. Deconvolution challenges in physiological systems are illustrated by simulated and real case studies.

Deconvolution

SPARACINO, GIOVANNI;PILLONETTO, GIANLUIGI;COBELLI, CLAUDIO
2013

Abstract

Deconvolution is a classic problem in many disciplines of engineering and science and frequently faced also in the study of physiological and pharmacokinetic systems. In this chapter, we first introduce the deconvolution problem for physiological systems and its inherent difficulties in a formal manner. Then, we present a detailed description of the regularization method, a classic nonparametric approach which has some significant advantages over other techniques, especially if it is embedded in a stochastic setting. Finally, other deconvolution methods, both parametric and nonparametric, are briefly reviewed. Deconvolution challenges in physiological systems are illustrated by simulated and real case studies.
2013
Modeling Methodology for Physiology and Medicine: Second Edition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2969102
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