
Radial Basis Functions
Theory and Implementations
Martin D. Buhmann(Author)
Cambridge University Press
Published on 12. February 2009
Book
Paperback/Softback
272 pages
978-0-521-10133-2 (ISBN)
Description
In many areas of mathematics, science and engineering, from computer graphics to inverse methods to signal processing, it is necessary to estimate parameters, usually multidimensional, by approximation and interpolation. Radial basis functions are a powerful tool which work well in very general circumstances and so are becoming of widespread use as the limitations of other methods, such as least squares, polynomial interpolation or wavelet-based, become apparent. The author's aim is to give a thorough treatment from both the theoretical and practical implementation viewpoints. For example, he emphasises the many positive features of radial basis functions such as the unique solvability of the interpolation problem, the computation of interpolants, their smoothness and convergence and provides a careful classification of the radial basis functions into types that have different convergence. A comprehensive bibliography rounds off what will prove a very valuable work.
Reviews / Votes
"A must read for anyone making direct use of this tool, and a must browse for anyone interested in keeping up with the state of the art in multivariate approximation theory in general." Computing ReviewsMore details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Product notice
Paperback (trade)
Illustrations
Worked examples or Exercises
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 17 mm
Weight
446 gr
ISBN-13
978-0-521-10133-2 (9780521101332)
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01/2005
1st Edition
Cambridge University Press
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07/2003
Cambridge University Press
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Content
Preface; 1. Introduction; 2. Summary of methods and applications; 3. General methods for approximation and interpolation; 4. Radial basis function approximation on infinite grids; 5. Radial basis functions on scattered data; 6. Radial basis functions with compact support; 7. Implementations; 8. Least squares methods; 9. Wavelet methods with radial basis functions; 10. Further results and open problems; Appendix; Bibliography; Index.