KL1p - A portable C++ library for Compressed Sensing

References and Resources

Emmanuel Candes and Justin Romberg

l1-MAGIC : Recovery of Sparse Signals via Convex Programming

Caltech, 2005
Joel A. Tropp and Anna C. Gilbert

Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit

IEEE Transactions on Information Theory, Vol.53, NO.12, 2007
D. Needell and R. Vershynin

Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit

IEEE J. Selected Topics in Signal Process., vol.4, pp.310-316, 2010
D. Needell and J.A. Tropp

CoSaMP: Iterative signal recovery from incomplete and inaccurate samples

Applied and Computational Harmonic Analysis, 2009
Wei Dai and Olgica Milenkovic

Subspace Pursuit for Compressive Sensing Signal Reconstruction

arXiv:0803.0811v3, 2009
G. Hosein Mohimani, Massoud Babaie-Zadeh and Christian Jutten

Smoothed L0 (SL0) Algorithm for Sparse Decomposition

http://ee.sharif.edu/~SLzero, 2008
D. L. Donoho, A. Maleki, and A. Montanari

Message-passing algorithms for compressed sensing

Proc. National Academy of the Sciences, vol.106, no.45, pp.18914-18919, 2009
F. Krzakala, M. Mezard, F. Sausset, Y. F. Sun and L. Zdeborova

Statistical-physics-based reconstruction in compressed sensing

arXiv:1109.4424v3, 2012
Conrad Sanderson

Armadillo: An Open Source C++ Linear Algebra Library for Fast Prototyping and Computationally Intensive Experiments

Technical Report, NICTA, 2010