A Comparative Study of Regression Methods for Solving the Timepix Calibration Task
- NázevTitle
- A Comparative Study of Regression Methods for Solving the Timepix Calibration TaskA Comparative Study of Regression Methods for Solving the Timepix Calibration Task
- Druh výsledkuResult type
- Článek v časopiseJournal article
- AutořiAuthors
- J. Broulím, M. Prokop, L. Nouzak, P. Smrčka
- Klíčová slovaKeywords
- Timepix, Timepix3, Timepix4, Levenberg-Marquardt, regression, optimization algorithms, variable projection, calibration
- DOIDOI
- 10.3390/s25216714
- Časopis / citaceJournal / citation
- Sensors 25(21), 6714 (2025) · ISSN 1424-8220
- RokYear
- 2025
- JazykLanguage
- eng
- ZáznamyRecords
- ProjektProject
- Institucionální podpora na rozvoj výzkumné org.Institucionální podpora na rozvoj výzkumné org.; Detektory ionizujícího záření ve fundamentálních experimentech a aplikovaném výzkumuDetectors of ionizing radiation in fundamental experiments and applied research
- Plný text (open access)Full text (open access)
- https://www.mdpi.com/1424-8220/25/21/6714/pdf?version=1762160684
- Citace ke staženíDownload citation
- TXT · BibTeX
AbstraktAbstract
In this article, we provide a study of the energy calibration model used for Timepix-type detectors. The Timepix detectors, operating in Time-over-Threshold mode, measure information that needs to be mapped into the corresponding energies using a non-linear function. We consider three iterative algorithms, Gradient-Descent, Gauss-Newton and Levenberg-Marquardt algorithm, which we modify according to the calibration model constraints to perform better in terms of the convergence properties. Moreover, based on the variable projection method, we suggest a partial linearization of the calibration problem and provide results for this novel method.
In this article, we provide a study of the energy calibration model used for Timepix-type detectors. The Timepix detectors, operating in Time-over-Threshold mode, measure information that needs to be mapped into the corresponding energies using a non-linear function. We consider three iterative algorithms, Gradient-Descent, Gauss-Newton and Levenberg-Marquardt algorithm, which we modify according to the calibration model constraints to perform better in terms of the convergence properties. Moreover, based on the variable projection method, we suggest a partial linearization of the calibration problem and provide results for this novel method.