NDLI: Asymptotic properties of the estimate refinement method in polyhedral approximation of multidimensional balls

Content Provider	Springer Nature Link
Author	Kamenev, G. K.
Copyright Year	2015
Abstract	The estimate refinement method for the polyhedral approximation of convex compact bodies is considered. In the approximation of convex bodies with a smooth boundary, this method is known to generate polytopes with an optimal order of growth of the number of vertices and facets depending on the approximation error. The properties of the method are examined as applied to the polyhedral approximation of a multidimensional ball. As vertices of approximating polytopes, the method is shown to generate a deep holes sequence on the surface of the ball. As a result, previously obtained combinatorial properties of convex hulls of the indicated sequences, namely, the convergence rates with respect to the number of faces of all dimensions and the optimal growth of the cardinality of the facial structure (of the norm of the f-vector) can be extended to such polytopes. The combinatorial properties of the approximating polytopes generated by the estimate refinement method are compared to the properties of polytopes with a facial structure of extremal cardinality. It is shown that the polytopes generated by the method are similar to stacked polytopes, on which the minimum number of faces of all dimensions is attained for a given number of vertices.
Starting Page	1619
Ending Page	1632
Page Count	14
File Format	PDF
ISSN	09655425
Journal	Computational Mathematics and Mathematical Physics
Volume Number	55
Issue Number	10
e-ISSN	15556662
Language	English
Publisher	Pleiades Publishing
Publisher Date	2015-10-17
Publisher Place	Moscow
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	convex bodies multidimensional ball polyhedral approximation estimate refinement method vertices facets faces facial structure f-vector convergence rate Computational Mathematics and Numerical Analysis
Content Type	Text
Resource Type	Article
Subject	Computational Mathematics

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