Parameter-Bounding Algorithms for Linear Errors-in-Variables Models

S. M. Veres and J. P. Norton
Additional contact information
S. M. Veres: University of Birmingham, School of Electronic and Electrical Engineering
J. P. Norton: University of Birmingham, School of Electronic and Electrical Engineering

Chapter 17 in Bounding Approaches to System Identification, 1996, pp 275-288 from Springer

Abstract: Abstract Computational techniques are considered for the errors-in-variables (EIV) problem with bounds specified on the errors in all variables. The significant difference in difficulty in bounding the parameters of a dynamic EIV model, compared with the static case, is explained. Conditions for the feasible set of the parameters to be the union of polytopes are discussed, and a search technique to find the nonlinear bounds for the dynamic EIV problem is described. A simulation example compares EIV and equation-error bounding. Techniques for shortening the computation of EIV parameter bounds, and for finding polytope and ellipsoid approximations, are given.

Keywords: Nonlinear Bound; Uncertain Variable; Parameter Bound; Sampling Instant; Ellipsoid Approximation (search for similar items in EconPapers)
Date: 1996
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-9545-5_17

Ordering information: This item can be ordered from
http://www.springer.com/9781475795455

DOI: 10.1007/978-1-4757-9545-5_17

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().