A fast algorithm to assess local structural identifiability
The paper presents a novel method for assessing the local structural identifiability question for a general non-linear state-space model. The method is a combination of (i) the application of a singular value decomposition to a parametric output sensitivity matrix that is created by simply integrati...
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| Published in | Automatica (Oxford) Vol. 58; pp. 118 - 124 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.08.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0005-1098 1873-2836 |
| DOI | 10.1016/j.automatica.2015.05.004 |
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| Abstract | The paper presents a novel method for assessing the local structural identifiability question for a general non-linear state-space model. The method is a combination of (i) the application of a singular value decomposition to a parametric output sensitivity matrix that is created by simply integrating the model once and, (ii) a symbolic computation for a reduced model that is guided by the SVD results and allows a confirmation of the conclusions regarding identifiability obtained in the first step. In case there is a lack of identifiability, the symbolic computation quickly results in determination of the exact structure of the nullspace and a suitable re-parametrisation. The method is discussed in detail and applied to three case studies, of which the last two are considerably large, containing 22 and 43 parameters to be identified, respectively. |
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| AbstractList | The paper presents a novel method for assessing the local structural identifiability question for a general non-linear state-space model. The method is a combination of (i) the application of a singular value decomposition to a parametric output sensitivity matrix that is created by simply integrating the model once and, (ii) a symbolic computation for a reduced model that is guided by the SVD results and allows a confirmation of the conclusions regarding identifiability obtained in the first step. In case there is a lack of identifiability, the symbolic computation quickly results in determination of the exact structure of the nullspace and a suitable re-parametrisation. The method is discussed in detail and applied to three case studies, of which the last two are considerably large, containing 22 and 43 parameters to be identified, respectively. |
| Author | Stigter, Johannes D. Molenaar, Jaap |
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article-title: Global identifiability of the parameters of nonlinear systems with specified inputs: A comparison of methods publication-title: Mathematical Biosciences doi: 10.1016/0025-5564(90)90055-4 |
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| Title | A fast algorithm to assess local structural identifiability |
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