Constructions of local orthonormal bases for classification and regression, (with R. R. Coifman), Comptes Rendus Acad. Sci. Paris, Série I , vol. 319, pp. 191-196, Jul. 1994.
Abstract
We describe extensions to the "best-basis" method to construct orthonormal
bases which either maximize a class separability for signal classification
problems or minimize an estimation error for regression problems.
These algorithms reduce the dimensionality of these problems by using basis
functions which are well localized in time-frequency plane as
feature extractors.
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