Compressive sensing predicts that sufficiently sparse vectors can be recovered from highly incomplete information. Efficient recovery methods such as 1-minimization find the sparse...
A belief-propagation decoder for low-density lattice codes, which represents messages explicitly as a mixture of Gaussians functions, is given. In order to prevent the mixture elem...
The canonical problem of solving a system of linear equations arises in numerous contexts in information theory, communication theory, and related fields. In this contribution, we ...
Ori Shental, Paul H. Siegel, Jack K. Wolf, Danny B...
— A rateless code—i.e., a rate-compatible family of codes—has the property that codewords of the higher rate codes are prefixes of those of the lower rate ones. A perfect fa...
Today, with the advances of computer storage and technology, there are huge datasets available, offering an opportunity to extract valuable information. Probabilistic approaches ...