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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Abstract 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
AbstractList 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
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
Author Pogudin, Gleb
Hong, Hoon
Ovchinnikov, Alexey
Yap, Chee
Author_xml – sequence: 1
  givenname: Hoon
  surname: Hong
  fullname: Hong, Hoon
  email: hong@ncsu.edu
  organization: Department of Mathematics
– sequence: 2
  givenname: Alexey
  surname: Ovchinnikov
  fullname: Ovchinnikov, Alexey
  email: aovchinnikov@qc.cuny.edu
  organization: Ph.D. Programs in Mathematics and Computer Science
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  givenname: Gleb
  surname: Pogudin
  fullname: Pogudin, Gleb
  email: pogudin.gleb@gmail.com
  organization: LIX, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris
– sequence: 4
  givenname: Chee
  surname: Yap
  fullname: Yap, Chee
  email: yap@cs.nyu.edu
  organization: Courant Institute
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Snippet Many real‐world processes and phenomena are modeled using systems of ordinary differential equations with parameters. Given such a system, we say that a...
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SubjectTerms Algorithms
Differential equations
Mathematical models
Ordinary differential equations
Parameter identification
Software
Title Global Identifiability of Differential Models
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fcpa.21921
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Volume 73
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