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Orthonormal bases of compactly supported wavelets
I. Daubechies · 1988
Earlier work this paper cites.
Ten Lectures on Wavelets
I. Daubechies · 1992
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Wavelets
A. K. Louis, P. Maaß, and A. Rieder · 1998
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New tight frames of curvelets and optimal representations of objects with piecewise C 2 {C}^{2} singularities
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D. L. Donoho · 2006
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SPGL1: A solver for large-scale sparse reconstruction, June 2007
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E. J. Candès · 2008
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A. Cohen, W. Dahmen, and R. Devore · 2009
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Counting faces of randomly-projected polytopes when the projection radically lowers dimension
D. L. Donoho and J. Tanner · 2009
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Exploiting structure in wavelet-based Bayesian compressive sensing
L. He and L. Carin · 2009
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M. A. Herman and T. Strohmer · 2009
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