Global Identifiability of Differential Models

Many real‐world processes and phenomena are modeled using systems of ordinary differential equations with parameters. Given such a system, we say that a parameter is globally identifiable if it can be uniquely recovered from input and output data. The main contribution of this paper is to provide th...

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Published inCommunications on pure and applied mathematics Vol. 73; no. 9; pp. 1831 - 1879
Main Authors Hong, Hoon, Ovchinnikov, Alexey, Pogudin, Gleb, Yap, Chee
Format Journal Article
LanguageEnglish
Published Melbourne John Wiley & Sons Australia, Ltd 01.09.2020
John Wiley and Sons, Limited
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Summary:Many real‐world processes and phenomena are modeled using systems of ordinary differential equations with parameters. Given such a system, we say that a parameter is globally identifiable if it can be uniquely recovered from input and output data. The main contribution of this paper is to provide theory, an algorithm, and software for deciding global identifiability. First, we rigorously derive an algebraic criterion for global identifiability (this is an analytic property), which yields a deterministic algorithm. Second, we improve the efficiency by randomizing the algorithm while guaranteeing the probability of correctness. With our new algorithm, we can tackle problems that could not be tackled before. A software based on the algorithm (called SIAN) is available at https://github.com/pogudingleb/SIAN. © 2020 Wiley Periodicals LLC
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content type line 14
ISSN:0010-3640
1097-0312
DOI:10.1002/cpa.21921