"Nonlinear wavelet approximation in anisotropic Besov spaces" by Christopher John Leisner
 

Nonlinear wavelet approximation in anisotropic Besov spaces

Christopher John Leisner, Purdue University

Abstract

We introduce new anisotropic wavelet decompositions associated with the smoothness β, β = (β1, …, βd), β 1, …, βd > 0 of multi-dimensional data as measured in anisotropic Besov spaces Bβ. We give the rate of compression of these wavelet decompositions of functions f ∈ Bβ. Finally, we prove that, among a general class of anisotropic wavelet decompositions of a function f ∈ Bβ the anisotropic wavelet decomposition associated with β yields the optimal rate of compression of the wavelet decomposition of f.

Degree

Ph.D.

Advisors

Lucier, Purdue University.

Subject Area

Mathematics

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