We address the problem of designing optimal quantizers for distributed source coding. The generality of our formulation includes both the symmetric and asymmetric scenarios, toget...
We address the problem of bounding below the probability of error under maximum-likelihood decoding of a binary code with a known distance distribution used on a binarysymmetric ch...
d Abstract) James Allen Fill1† 1 Department of Applied Mathematics and Statistics, The Johns Hopkins University, 34th and Charles Streets, Baltimore, MD 21218-2682 USA received 2...
Abstract –In this paper, a variational message passing framework is proposed for Markov random fields, which is computationally more efficient and admits wider applicability comp...
In this work, we show how expectation maximization based simultaneous channel and noise estimation can be derived without a vector Taylor series expansion. The central idea is to ...
Friedrich Faubel, John W. McDonough, Dietrich Klak...