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- Simon Foucart, Holger Rauhut
- Applied and Numerical Harmonic Analysis
- 2013

â€¢ Page 48, Lines 26 and 31: replace â€˜s-sparse x âˆˆ CN â€™ by â€˜x âˆˆ CN with â€–xâ€–0 = sâ€™, otherwise the implication (b)â‡’ (a) may not be true â€¢ Page 51, Theorem 2.15: the statement concerns s-sparse vectors,â€¦ (More)

- Yonina C. Eldar, Holger Rauhut
- IEEE Transactions on Information Theory
- 2010

This paper considers recovery of jointly sparse multichannel signals from incomplete measurements. Several approaches have been developed to recover the unknown sparse vectors from the givenâ€¦ (More)

- Holger Rauhut, Karin Schnass, Pierre Vandergheynst
- IEEE Transactions on Information Theory
- 2008

This paper extends the concept of compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, which is a composition ofâ€¦ (More)

- Massimo Fornasier, Holger Rauhut
- SIAM J. Numerical Analysis
- 2008

Vector valued data appearing in concrete applications often possess sparse expansions with respect to a preassigned frame for each vector component individually. Additionally, different componentsâ€¦ (More)

- Georg TaubÃ¶ck, Franz Hlawatsch, Daniel Eiwen, Holger Rauhut
- IEEE Journal of Selected Topics in Signalâ€¦
- 2010

We consider the application of compressed sensing (CS) to the estimation of doubly selective channels within pulse-shaping multicarrier systems (which include orthogonal frequency-divisionâ€¦ (More)

- Massimo Fornasier, Holger Rauhut, Rachel Ward
- SIAM Journal on Optimization
- 2011

We present and analyze an efficient implementation of an iteratively reweighted least squares algorithm for recovering a matrix from a small number of linear measurements. The algorithm is designedâ€¦ (More)

- Massimo Fornasier, Holger Rauhut
- Handbook of Mathematical Methods in Imaging
- 2015

Compressive sensing is a new type of sampling theory, which predicts that sparse signals and images can be reconstructed from what was previously believed to be incomplete information. As a mainâ€¦ (More)

- Petros Boufounos, Gitta Kutyniok, Holger Rauhut
- IEEE Transactions on Information Theory
- 2011

Sparse representations have emerged as a powerful tool in signal and information processing, culminated by the success of new acquisition and processing techniques such as compressed sensing (CS).â€¦ (More)

- Holger Rauhut, Rachel Ward
- Journal of Approximation Theory
- 2012

We consider the problem of recovering polynomials that are sparse with respect to the basis of Legendre polynomials from a small number of random samples. In particular, we show that a Legendreâ€¦ (More)

- Felix Krahmer, Shahar Mendelson, Holger Rauhut
- ArXiv
- 2014

The theory of compressed sensing considers the following problem: Let A âˆˆ CmÃ—n and let x âˆˆ C be s-sparse, i.e., xi = 0 for all but s indices i. One seeks to recover x uniquely and efficiently fromâ€¦ (More)