Approximation Theory and Algorithms for Data Analysis

Armin Iske

ISBN 10: 3030052273 / ISBN 13: 9783030052270

Published by Springer International Publishing, Springer International Publishing Jan 2019, 2019

About this Item

Neuware -This textbook offers an accessible introduction to the theory and numerics of approximation methods, combining classical topics of approximation with recent advances in mathematical signal processing, and adopting a constructive approach, in which the development of numerical algorithms for data analysis plays an important role.The following topics are covered:\* least-squares approximation and regularization methods\* interpolation by algebraic and trigonometric polynomials\* basic results on best approximations\* Euclidean approximation\* Chebyshev approximation\* asymptotic concepts: error estimates and convergence rates\* signal approximation by Fourier and wavelet methods\* kernel-based multivariate approximation\* approximation methods in computerized tomographyProviding numerous supporting examples, graphical illustrations, and carefully selected exercises, this textbook is suitable for introductory courses, seminars, and distance learning programs on approximation for undergraduate students.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 368 pp. Englisch.

Seller Inventory # 9783030052270

Bibliographic Details

• Title: Approximation Theory and Algorithms for Data Analysis
• Publisher: Springer International Publishing, Springer International Publishing Jan 2019
• Publication Date: 2019
• Language: English
• ISBN 10: 3030052273
• ISBN 13: 9783030052270
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 26D millimeters 241 millimeters width by 160 millimeters height by 26 millimeters depth
• Weight: 717 grams

About this title

Synopsis

This textbook offers an accessible introduction to the theory and numerics of approximation methods, combining classical topics of approximation with recent advances in mathematical signal processing, and adopting a constructive approach, in which the development of numerical algorithms for data analysis plays an important role.

The following topics are covered:

* least-squares approximation and regularization methods

* interpolation by algebraic and trigonometric polynomials

* basic results on best approximations

* Euclidean approximation

* Chebyshev approximation

* asymptotic concepts: error estimates and convergence rates

* signal approximation by Fourier and wavelet methods

* kernel-based multivariate approximation

* approximation methods in computerized tomography

Providing numerous supporting examples, graphical illustrations, and carefully selected exercises, this textbook is suitable for introductory courses, seminars, and distance learning programs on approximation for undergraduate students.

About the Author

Armin Iske is professor of numerical approximation at the Department of Mathematics of the University of Hamburg.