Overview
Covers general approximation methods on linear positive operators
Provides key results on study of convergence, its direct results, rate of convergence, and asymptotic behavior
Presents convergence in real and complex domains
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Reviews
From the book reviews:
“Within the field of approximation theory, the book deals with convergence results mainly for linear positive operators, an area of intensive research in the last few decades. It turns out to be a very useful tool for beginners and all those researchers interested in the aforesaid mathematical subject.” (Daniel Cárdenas-Morales, zbMATH, Vol. 1295, 2014)
“This monograph should be accessible to anyone familiar with the fundamentals of approximation theory, measure theory and functional analysis. The exposition is essentially self-contained. From this point of view, the book is of great interest to mathematicians and computer scientists working in the field of approximation theory and in related application areas.” (Octavian Agratini, Mathematical Reviews, August, 2014)Authors and Affiliations
Bibliographic Information
Book Title: Convergence Estimates in Approximation Theory
Authors: Vijay Gupta, Ravi P. Agarwal
DOI: https://doi.org/10.1007/978-3-319-02765-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-02764-7Published: 23 January 2014
Softcover ISBN: 978-3-319-35013-4Published: 27 August 2016
eBook ISBN: 978-3-319-02765-4Published: 08 January 2014
Edition Number: 1
Number of Pages: XIII, 361
Topics: Approximations and Expansions, Operator Theory, Analysis, Partial Differential Equations