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research article

Wavelets, Fractals, and Radial Basis Functions

Blu, T.  
•
Unser, M.  
2002
IEEE Transactions on Signal Processing

Wavelets and radial basis functions (RBFs) lead to two distinct ways of representing signals in terms of shifted basis functions. RBFs, unlike wavelets, are nonlocal and do not involve any scaling, which makes them applicable to nonuniform grids. Despite these fundamental differences, we show that the two types of representation are closely linked together …through fractals. First, we identify and characterize the whole class of self-similar radial basis functions that can be localized to yield conventional multiresolution wavelet bases. Conversely, we prove that for any compactly supported scaling function φ(x), there exists a one-sided central basis function $ \rho _{ + }(x) $ that spans the same multiresolution subspaces. The central property is that the multiresolution bases are generated by simple translation of $ \rho _{ + } $ without any dilation. We also present an explicit time-domain representation of a scaling function as a sum of harmonic splines. The leading term in the decomposition corresponds to the fractional splines: a recent, continuous-order generalization of the polynomial splines.

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Type
research article
DOI
10.1109/78.984733
Web of Science ID

WOS:000173968500008

Author(s)
Blu, T.  
•
Unser, M.  
Date Issued

2002

Publisher

IEEE

Published in
IEEE Transactions on Signal Processing
Volume

50

Issue

3

Start page

543

End page

553

Subjects

Wavelets and Fractals

Note

IEEE Signal Processing Society's 2003 Best Paper Award

URL

URL

http://bigwww.epfl.ch/publications/blu0201.ps

URL

http://bigwww.epfl.ch/publications/blu0201.html
Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LIB  
Available on Infoscience
November 30, 2005
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/220692
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