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Approximation Theory and Algorithms for Data Analysis

Autor: Armin Iske

Limbă:

Legare: Copertă tare

Editura: Springer Nature Switzerland AG

Disponibilitate: În depozitul extern

Expediem în 10-13 zile

325.90 lei

This textbook offers an accessible introduction to the theory and numerics of approximation methods,...

Informații despre carte

Autor

Armin Iske

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2019

Pagini

358

EAN

9783030052270

Enbook ID

20745796

Editura

Springer Nature Switzerland AG

Greutate

736

Dimensiuni

166 x 242 x 22

Descriere completă

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.