High - Dimensional Wavelet
نویسنده
چکیده
Wavelets can be thought of as a set of well-localized basis functions with very good approximation properties. The diiculty in applying wavelet approximation to high-dimensional data is that the number of basis functions increases exponentially with the number of dimensions, making the application of standard mathematical methods for determining coeecients diic ult. We propose a modeling methodology that uses multidimensional cubic B-spline wavelets whose co eecients are determined by a nonlinear optimization procedure that combines simulated anneali ng with hill climbing.
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