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Abstract:
A wavelet basis selection procedure is presented for wavelet
regression. Both the basis and threshold are selected using
cross-validation. The method includes the capability of
incorporating prior knowledge on the smoothness (or shape of the
basis functions) into the basis selection procedure. The results of
the method are demonstrated using widely published sampled
functions. The results of the method are contrasted with other
basis function based methods.
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