Approximation Theory and Algorithms for Data Analysis is popular PDF and ePub book, written by Armin Iske in 2018-12-14, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Approximation Theory and Algorithms for Data Analysis can be Read Online from any device for your convenience.
Approximation Theory and Algorithms for Data Analysis Book PDF Summary
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.
Detail Book of Approximation Theory and Algorithms for Data Analysis PDF
- Author : Armin Iske
- Release : 14 December 2018
- Publisher : Springer
- ISBN : 9783030052287
- Genre : Mathematics
- Total Page : 358 pages
- Language : English
- PDF File Size : 11,8 Mb
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