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We prove optimal embeddings for nonlinear approximation spaces Aq , in terms of weighted Lorentz sequence spaces, with the weights depending on the democracy functions of the basis. As applications we recover known embeddings for N -term wavelet approximation in L, Orlicz, and Lorentz norms. We also study the “greedy classes” G α q introduced by Gribonval… (More)
We study the efficiency of the greedy algorithm for wavelet bases in Lorentz spaces in order to give the near best approximation. The result is used to give sharp inclusions for the approximation spaces in terms of discrete Lorentz sequence spaces. Constr. Approx. 33 (2011), no. 1, 1--14
We compute the democracy functions associated with wavelet bases in general Lorentz spaces Λw and Λ q,∞ w , for general weights w and 0 < q <∞.