𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Algorithms for optimal errors-in-variables filtering

✍ Scribed by Roberto Diversi; Roberto Guidorzi; Umberto Soverini

Book ID
104300548
Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
170 KB
Volume
48
Category
Article
ISSN
0167-6911

No coin nor oath required. For personal study only.

✦ Synopsis

This paper introduces a new algorithm for optimal ΓΏltering of data generated by errors-in-variables processes and compares its e ciency with that of two previous algorithms (Optimal errors-in-variables ΓΏltering, to appear in Automatica). It is shown that the new approach proposed here, based on the Cholesky decomposition of a matrix, is characterized by a high level of e ciency, superior to the e ciency of all other algorithms. An expression of the expected performance of the ΓΏltering algorithms is also developed; a Monte Carlo simulation conΓΏrms its accuracy.

πŸ“œ SIMILAR VOLUMES

Convergence properties of bias-eliminati
Convergence properties of bias-eliminating algorithms for errors-in-variables identification
✍ Torsten SΓΆderstrΓΆm; Mei Hong; Wei Xing Zheng πŸ“‚ Article πŸ“… 2005 πŸ› John Wiley and Sons 🌐 English βš– 174 KB πŸ‘ 2 views

This paper considers the problem of dynamic errors-in-variables identification. Convergence properties of the previously proposed bias-eliminating algorithms are investigated. An error dynamic equation for the bias-eliminating parameter estimates is derived. It is shown that the convergence of the b

Error analysis algorithms for distribute
Error analysis algorithms for distributed parameter filtering
✍ G.R.V. Kumar; A.P. Sage πŸ“‚ Article πŸ“… 1972 πŸ› Elsevier Science 🌐 English βš– 307 KB

Interest in estimation in distributed parameter linear systems is increasing. Unfortunately, algorithms for filtering in distributed parameter systems are quite complex and thus suboptimization will often, in practice, be necessary. Also incorrect models for distributed processes and prior statistic

On dependent variables and instrumental
On dependent variables and instrumental errors in filtering of experimental data
✍ Lukasiewicz, S. A. ;Babaei, R. πŸ“‚ Article πŸ“… 1996 πŸ› John Wiley and Sons 🌐 English βš– 497 KB πŸ‘ 3 views

The paper presents a filtering algorithm which corrects the results of measurements of certain physical quantities if some information about the model of the system is known. The results of measurements are not only obtained in an explicit form for the considered variable but also in a form of depen