technical report On parameter identifiability of non-linear time-continuous systems


Abstract

Identifiability is a fundamental prerequisite for model identification. It concerns uniqueness of the model parameters determined from experimental observations. This paper specifically deals with structural or a priori identifiability: whether or not parameters can be identified from a given model structure and experimental measurements. Since experimental data are usually affected by uncertainties this question is known as "practical identifiability". In this report, we review some definitions and methods of parameter identifiability based on the observability rank test suitable extended to handle noisy observations. This method is used to test a priori identifiability of parameters in many non-linear biological processes.



Paper Details

Authors

P. Lecca

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/var/papers/TR/TR-11-2010.pdf

Language

English
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