Identifiability of Model Parameter
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Numerous techniques for performing structural identifiability analysis on linear parametric models exist, and this is a well-understood topic.
“Numerous techniques for performing a structural identifiability analysis on linear parametric models exist, and this is a well‐understood topic.46, 47, 48”
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- Authors
- Godfrey, K. R., & DiStefano, J. J.
- Affiliations
- University of Warwick (GB)
- University of California, Los Angeles (US)
- ORCID
- Godfrey, K.R.
- Venue
- IFAC Proceedings Volumes
- Publisher
- Elsevier BV
- Published
- 1985-07
- Volume
- 18
- Issue
- 5
- Pages
- 89-114
- ISSN
- 1474-6670 (ISSN-L)
- OpenAlex
- W2738906282
- Cited by
- 170
- References
- 46
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 2 · 2023: 6 · 2022: 4 · 2021: 3 · 2020: 4 · 2019: 4 · 2017: 4 · 2016: 1 · 2015: 3 · 2014: 1 · 2013: 4 · 2012: 8
- FWCI
- 10.04
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IFAC Proceedings Volumes (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Keywords
- parameter identifiability, structural identifiability, linear time-invariant systems, nonlinear models, time-varying systems, Taylor series expansion, noisy data, parameter estimation accuracy, compartmental systems, microbial growth modeling
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