We derive entropy bounds for the absolute convex hull of vectors in and apply this to the case where is the -fold tensor matrix with a given , normalized to that for all . For we let be the linear space with smallest dimension such that . We call the -approximation of and assume it is – up to log terms – polynomial in . We show that the entropy of the absolute convex hull of the -fold tensor matrix is up to log-terms of the same order as the entropy for the case . The results are generalized to absolute convex hulls of tensors of functions in where is Lebesgue measure on . As an application we consider the space of functions on with bounded -th order Vitali total variation for a given . As a by-product, we construct an orthonormal, piecewise polynomial, wavelet dictionary for functions that are well-approximated by piecewise polynomials.

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