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- David L. Donoho
- IEEE Transactions on Information Theory
- 2006

Suppose x is an unknown vector in Ropfm (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform codingâ€¦ (More)

- Scott Saobing Chen, David L. Donoho, Michael A. Saunders
- SIAM J. Scientific Computing
- 1998

- David L. Donoho
- IEEE Trans. Information Theory
- 1995

Donoho and Johnstone (1992a) proposed a method for reconstructing an unknown function f on [0; 1] from noisy data di = f(ti) + zi, i = 0; : : : ; n 1, ti = i=n, zi iid N(0; 1). The reconstruction fÌ‚â€¦ (More)

With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, variable knot spline, orâ€¦ (More)

- Michael Lustig, David L. Donoho, John M Pauly
- Magnetic resonance in medicine
- 2007

The sparsity which is implicit in MR images is exploited to significantly undersample k-space. Some MR images such as angiograms are already sparse in the pixel representation; other, moreâ€¦ (More)

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions ofâ€¦ (More)

- Emmanuel J. CandÃ¨s, Laurent Demanet, David L. Donoho, Lexing Ying
- Multiscale Modeling & Simulation
- 2006

This paper describes two digital implementations of a new mathematical transform, namely, the second generation curvelet transform in two and three dimensions. The first digital transformation isâ€¦ (More)

- David L. Donoho, Arian Maleki, Andrea Montanari
- Proceedings of the National Academy of Sciencesâ€¦
- 2009

Compressed sensing aims to undersample certain high-dimensional signals yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to beâ€¦ (More)

- David L. Donoho, Michael Elad
- Proceedings of the National Academy of Sciencesâ€¦
- 2003

Given a dictionary D = {d(k)} of vectors d(k), we seek to represent a signal S as a linear combination S = summation operator(k) gamma(k)d(k), with scalar coefficients gamma(k). In particular, we aimâ€¦ (More)

- David L. Donoho, Michael Elad, Vladimir N. Temlyakov
- IEEE Transactions on Information Theory
- 2006

Overcomplete representations are attracting interest in signal processing theory, particularly due to their potential to generate sparse representations of signals. However, in general, the problemâ€¦ (More)