Global Identifiability of Differential Models |
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| Authors: | Hoon Hong Alexey Ovchinnikov Gleb Pogudin Chee Yap |
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| Affiliation: | 1. North Carolina State University, Department of Mathematics, Box 8205, Raleigh, NC, 27695 USA;2. CUNY Queens College, Department of Mathematics, 65-30 Kissena Blvd., Queens, NY, 11367 USA;3. National Research University, Higher School of Economics, Department of Computer Science, 11 Pokrovsky blvd, Moscow, 109028 Russia;4. Courant Institute, 251 Mercer Street, New York, NY, 10012 USA |
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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 |
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