I just came across a CS solver written in R as shown in this presentation: Compressive Sampling with R: A Tutorial by Mehmet Suzen. The R1Magic package is here. A reference manual is here.
YALL1 now include a group sparsity solving capability. Let us look at what he can do. From the webpage:
YALL1 package now includes:
solves the following L1-minimization problems:
(BP) min ||Wx||w,1 s.t. Ax = b
(L1/L1) min ||Wx||w,1 + (1/ν)||Ax - b||1 (L1/L2) min ||Wx||w,1 + (1/2ρ)||Ax - b||22 (L1/L2con) min ||Wx||w,1, s.t. ||Ax - b||2 <= δ
(BP+) min ||x||w,1 s.t. Ax = b and x >= 0
(L1/L1+) min ||x||w,1 + (1/ν)||Ax - b||1 s.t. x >= 0
(L1/L2+) min ||x||w,1 + (1/2ρ)||Ax - b||22 s.t. x >= 0
(L1/L2con+) min ||x||w,1, s.t. ||Ax - b||2 <= δ, x >= 0
Go to discussions and Q&As.
The group sparsity code solves the following model
(GroupBP) min sumi wi ||x_gi||2 s.t. Ax = b
where g1, g2, … are groups of coordinates and w1,w2, … are their weights.
Joint sparsity is a special case of group sparsity for recovering X = [x1,x2, ..., xl] where the xi‘s share a common sparse support.
(JointBP) min sumi wi ||Xi,:||2 s.t. AX = B.
Yin Zhang*, Wei Deng, Junfeng Yang, and Wotao Yin.
* The original author of YALL1 (beta 1 – 6).
YALL1 Basic: Alternating Direction Algorithms for L1 Problems in Compressive Sensing, Rice CAAM Report TR09-37, 2009.
YALL1 Group/Joint Sparsity: Group Sparse Optimization by Alternating Direction Method, Rice CAAM Report TR11-06, 2011.
YALL1 is now open-source. It is distributed under the terms of the GNU General Public License. [Proceed to the download page]
Credit Video: ESA/DLR/FU Berlin (G. Neukum), via the Planetary Society blog.
Phobos ( a moon of Mars) slips past Jupiter, On June 1 2011, Mars express watched as Phobos (the inner and larger of Mars' two moons) slipped past distant Jupiter. Mars Express is studying Phobos to help the Russian Phobos-Grunt mission prepare to land on the moon and grab a sample for return to Earth. Credit: ESA/DLR/FU Berlin (G. Neukum)