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Compactly supported radial basis functions: how and why?

Abstract:

The use of radial basis functions have attracted increasing attention in recent years as an elegant scheme for high-dimensional scattered data approximation, an accepted method for machine learning, one of the foundations of mesh-free methods, an alternative way to construct higher order methods for solving partial differential equations (PDEs), an emerging method for solving PDEs on surfaces, a novel method for mesh repair and so on. All these applications share one mathematical foundation: ...

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Publication date:
2012-01-01
UUID:
uuid:698c1230-9719-455f-a486-80eb9ed80163
Local pid:
oai:eprints.maths.ox.ac.uk:1561
Deposit date:
2012-07-20

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