Best Approximation With Geometric Constraints

<p>This is a study of best approximation with certain geometric constraints. Two major problem areas are considered: best L_p approximation to a function in L_p(0,1) by convex functions, (m, n)-convex functions, (m, n)-convex functions and (m, n)-convex splines, for 1 < p < ∞ , and best uniform approximation to a continuous function by convex functions, quasi-convex functions and piecewise monotone functions.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Mathematics & Statistics

Year dc:date.available

1989

Author dc:creator

• Xu, Yuesheng

Contributors dc:contributor

• S. E. Weinstein
• M. Bartelt
• John Swetits
• Hideaki Kaneko

• Approximation theory
• Geometrical constructions
• Mathematics

Statement dc:rights

• <p>In Copyright. URI: <a href="http://rightsstatements.org/vocab/InC/1.0/">http://rightsstatements.org/vocab/InC/1.0/</a> This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).</p>

Repository record dc:identifier

https://digitalcommons.odu.edu/mathstat_etds/106

OAI identifier oai:identifier

oai:digitalcommons.odu.edu:mathstat_etds-1110