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Comparison of three Frisch methods for errors-in-variables identification
- Source :
- IFAC Proceedings Volumes. 41:414-419
- Publication Year :
- 2008
- Publisher :
- Elsevier BV, 2008.
-
Abstract
- The errors–in–variables framework concerns static or dynamic systems whose input and output variables are affected by additive noise. Several estimation methods have been proposed for identifying dynamic errors–in–variables models. One of the more promising approaches is the so–called Frisch scheme. This paper decribes three different estimation criteria within the Frisch context and compares their estimation accuracy on the basis of the asymptotic covariance matrices of the estimates. Some numerical examples support well the theoretical results.
- Subjects :
- Estimation
SYSTEM IDENTIFICATION
Basis (linear algebra)
Computer science
Linear system
System identification
Context (language use)
General Medicine
Dynamical system
LINEAR SYSTEMS
DYNAMIC FRISCH SCHEME
ERRORS–IN–VARIABLES MODELS
Matrix (mathematics)
Identification (information)
Noise
Control theory
Errors-in-variables models
Algorithm
Subjects
Details
- ISSN :
- 14746670
- Volume :
- 41
- Database :
- OpenAIRE
- Journal :
- IFAC Proceedings Volumes
- Accession number :
- edsair.doi.dedup.....a02ccb4aee1ad68aa24c7e5dd29026e0