Geintra

 In this page we will include links and resources related to compressive sensing. Most of the material has been provided by Daniel Pizarro.

• Nice papers:
  • Imaging via compressive sampling, IEEE Signal Processing Magazine 2008. An Introduction to compressive sampling and recovery via convex programming (local copy).
  • From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images (local copy), describing issues when representing sparse signals, including the completeness theorems.
  • Optimization with Sparsity-Inducing Penalties (local copy)
• Related sites:
  • http://dsp.rice.edu/cs with lot of useful information and resources related to CS.
• Optimization toolboxes (all of them are installed in the cluster):
  • yall1 (http://yall1.blogs.rice.edu/), the toolbox main page. The users guide can be found at http://www.caam.rice.edu/~zhang/reports/tr0917.pdf (local copy). They have also a version for group sparse optimization.
  • l1_ls (http://www.stanford.edu/~boyd/l1_ls/), con manual de usuario en en http://www.stanford.edu/~boyd/l1_ls/l1_ls_usrguide.pdf (copia local) and explained in the  corresponding paper.
  • yalmip (http://users.isy.liu.se/johanl/yalmip/) 
  • sparselab (sparselab.stanford.edu/), described in the corresponding document.
• Msc & PhD Thesis:
  • Msc: A Sparse Signal Reconstruction Perspective for Source Localization with Sensor Arrays (local copy)
• MIsc:
  • Jose Velasco PhD Proposal