Abstract
Many methods have been developed for solving problems arising in mathematics and physics which are formulated in such a way as to require a point solution (e.g., a real number or vector). However, because of the uncertainty attached to the data and numerical errors induced by the finite-word-length representation in the computer, these methods are generally not appropriate to accurately characterize the uncertainty with which the solution is obtained. It is then difficult to assess the validity of the result.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
L. Pronzato and E. Walter, Math. Comput. Simul. 32, 571 (1990).
R. E. Moore, Methods and Applications of Interval Analysis, SIAM, Philadelphia, PA (1979).
A. Neumaier, Interval Methods for Systems of Equations, Cambridge University Press, Cambridge, United Kingdom (1990).
A. Ratschek and J. Rokne, New Computer Methods for Global Optimization, Ellis Horwood Limited, John Wiley & Sons, New York (1988).
IBM, High-Accuracy Arithmetic Subroutine Library, (ACRITH): Program Description and User’s Guide, SC 33-6164-02, 3rd Ed. (1986).
R. Klate, U. W. Kulisch, M. Neaga, D. Ratz, and C. Ullrich, PASCAL-XSC: Language Reference with Examples, Springer-Verlag, Heidelberg, Germany (1992).
L. Jaulin and E. Walter, Automatica 29, 1053 (1993).
L. Jaulin and E. Walter, Math. Comput. Simul. 35, 123 (1993).
R. E. Moore, Math. Comput. Simul. 34, 113 (1992).
M. Milanese and A. Vicino, Automatica 27, 403 (1991).
E. Walter and L. Jaulin, IEEE Trans. Autom. Control 39, 886 (1994).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1996 Springer Science+Business Media New York
About this chapter
Cite this chapter
Jaulin, L., Walter, É. (1996). Guaranteed Nonlinear Set Estimation via Interval Analysis. In: Milanese, M., Norton, J., Piet-Lahanier, H., Walter, É. (eds) Bounding Approaches to System Identification. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9545-5_23
Download citation
DOI: https://doi.org/10.1007/978-1-4757-9545-5_23
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-9547-9
Online ISBN: 978-1-4757-9545-5
eBook Packages: Springer Book Archive