Sharpening Interval Computations

Sharpening Interval Computations We consider ways to use monotonicity to reduce the excess width (due to dependence) of computed intervals. Use of monotonicity generally involves evaluation of a derivative. We show how monotonicity can often be used without evaluating derivatives. As examples, we show how Gaussian elimination and evaluation of slopes can be sharpened. A variable amount of extra computing is required to obtain the sharper results. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Reliable Computing Springer Journals

Sharpening Interval Computations

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2006 by Springer Science + Business Media, Inc.
Subject
Mathematics; Numeric Computing; Approximations and Expansions; Computational Mathematics and Numerical Analysis; Mathematical Modeling and Industrial Mathematics
ISSN
1385-3139
eISSN
1573-1340
D.O.I.
10.1007/s11155-006-2967-6
Publisher site
See Article on Publisher Site

Abstract

We consider ways to use monotonicity to reduce the excess width (due to dependence) of computed intervals. Use of monotonicity generally involves evaluation of a derivative. We show how monotonicity can often be used without evaluating derivatives. As examples, we show how Gaussian elimination and evaluation of slopes can be sharpened. A variable amount of extra computing is required to obtain the sharper results.

Journal

Reliable ComputingSpringer Journals

Published: Jan 1, 2006

References

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