Description: Approximation Theory and Algorithms for Data Analysis Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Armin Iske Format: Hardback Publisher: Springer Nature Switzerland AG, Switzerland Imprint: Springer Nature Switzerland AG ISBN-13: 9783030052270, 978-3030052270 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.
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Location: Aldershot
End Time: 2024-12-04T08:47:12.000Z
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Book Title: Approximation Theory and Algorithms for Data Analysis
Number of Pages: 358 Pages
Language: English
Publication Name: Approximation Theory and Algorithms for Data Analysis
Publisher: Springer Nature Switzerland A&G
Publication Year: 2019
Subject: Mathematics
Item Height: 235 mm
Item Weight: 717 g
Type: Textbook
Author: Armin Iske
Series: Texts in Applied Mathematics
Item Width: 155 mm
Format: Hardcover
