Version 1.1, Mar. 6, 2016
Implementations by Huynh Van Luong, Email: huynh.luong@fau.de
Multimedia Communications and Signal Processing, University of Erlangen-Nuremberg.
Please see LICENSE for the full text of the license.
I. Reconstruction Algorithm with Multiple Side Information (RAMSI)
Please cite this publication:
H. V. Luong, J. Seiler, A. Kaup, and S. Forchhammer, "A Reconstruction Algorithm with Multiple Side Information for Distributed Compression of Sparse Sources," in Data Compression Conference 2016 (DCC 2016), Snowbird, Utah, Apr. 2016.
Solving the n-l1 minimization problem:
(1)
Inputs:
: A vector of observations/data
: A measurement matrix
: Multiple side information signals
Outputs:
: The recovered source
Source code files:
- ramsi.m: The function for RAMSI
- usageDemo_ramsi.m: One demo to run RAMSI
II. Measurement Bounds for Weighted n-l1 Minimization
Please cite this publication:
H. V. Luong, J. Seiler, A. Kaup, S. Forchhammer, and N. Deligiannis, "Sparse Signal Recovery with Multiple Prior Information: Algorithm and Measurement Bounds," Signal Processing, vol. 152, pp. 417-428, Nov. 2018.
Computing the measurement bound m, which is required for successful reconstruction, for the weighted n-l1 minimization problem in (1).
(For details, please refer to the above reference)
Source code files:
- nl1Bound.m: The function for computing measurement bounds
- usageDemo_nl1Bound.m: One demo to run the nl1Bound function