Model-based Compressive Sensing Toolbox v1.1

New release: Feb 2012
Fixes minor bugs. Check the README for details.

* Each folder in the package consists of a CS recovery algorithm based on a particular signal model, and a script that tests that recovery algorithm. The names of the scripts typically end with '_example.m'
* Most of the code is plain Matlab code.
Each m-file starts with a header that contains a brief description of its I/O interface, details of extra software needed for its proper functioning, known problems with code usage, and any additional references to newer, published papers. Therefore, it is important that you carefully read the header of any function that you plan to use. Check the README file in the top folder for more details on usage and pest control.

Authors: Richard G. Baraniuk, Volkan Cevher, Marco F. Duarte, Chinmay Hegde

Related Research at Rice: Model-based compressive sensing

Copyright ©2012, DSP Group, Rice University

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