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＜電子ブック＞
Approximation Theory and Algorithms for Data Analysis / by Armin Iske
(Texts in Applied Mathematics. ISSN:21969949 ; 68)

版	1st ed. 2018.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2018
本文言語	英語
大きさ	X, 358 p. 34 illus., 15 illus. in color : online resource
著者標目	*Iske, Armin author SpringerLink (Online service)
件　名	LCSH:Approximation theory LCSH:Mathematics -- Data processing  全ての件名で検索 LCSH:Signal processing FREE:Approximations and Expansions FREE:Computational Mathematics and Numerical Analysis FREE:Signal, Speech and Image Processing
一般注記	1 Introduction -- 2 Basic Methods and Numerical Analysis -- 3 Best Approximations -- 4 Euclidean Approximations -- 5 Chebyshev Approximations -- 6 Asymptotic Results -- 7 Basic Concepts of Signal Approximation -- 8 Kernel-Based Approximation -- 9 Computational Topology -- References -- Subject Index -- Name Index 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 HTTP:URL=https://doi.org/10.1007/978-3-030-05228-7

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