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Bases in Function Spaces, Sampling, ...

Triebel, Hans,

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Bases in Function Spaces, Sampling, Discrepancy, Numerical integration

Record Type:	Electronic resources : Monograph/item
Title/Author:	Bases in Function Spaces, Sampling, Discrepancy, Numerical integration/ Hans Triebel
Author:	Triebel, Hans,
Published:	Zuerich, Switzerland :European Mathematical Society Publishing House, : 2010,
Description:	1 online resource (305 pages)
Subject:	Numerical analysis -
Online resource:	https://doi.org/10.4171/085
Online resource:	https://www.ems-ph.org/img/books/triebel_mini2.jpg
ISBN:	9783037195857

Bases in Function Spaces, Sampling, Discrepancy, Numerical integration
Triebel, Hans,

Bases in Function Spaces, Sampling, Discrepancy, Numerical integration[electronic resource] /Hans Triebel - Zuerich, Switzerland :European Mathematical Society Publishing House,2010 - 1 online resource (305 pages) - EMS Tracts in Mathematics (ETM)11.

Restricted to subscribers:https://www.ems-ph.org/ebooks.php

The first chapters of this book deal with Haar bases, Faber bases and some spline bases for function spaces in Euclidean n-space and n-cubes. This is used in the subsequent chapters to study sampling and numerical integration preferably in spaces with dominating mixed smoothness. The subject of the last chapter is the symbiotic relationship between numerical integration and discrepancy, measuring the deviation of sets of points from uniformity. This book is addressed to graduate students and mathematicians having a working knowledge of basic elements of function spaces and approximation theory, and who are interested in the subtle interplay between function spaces, complexity theory and number theory (discrepancy).

ISBN: 9783037195857

Standard No.: 10.4171/085doiSubjects--Topical Terms:

1245518
Numerical analysis

Bases in Function Spaces, Sampling, Discrepancy, Numerical integration
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520 $a The first chapters of this book deal with Haar bases, Faber bases and some spline bases for function spaces in Euclidean n-space and n-cubes. This is used in the subsequent chapters to study sampling and numerical integration preferably in spaces with dominating mixed smoothness. The subject of the last chapter is the symbiotic relationship between numerical integration and discrepancy, measuring the deviation of sets of points from uniformity. This book is addressed to graduate students and mathematicians having a working knowledge of basic elements of function spaces and approximation theory, and who are interested in the subtle interplay between function spaces, complexity theory and number theory (discrepancy).
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