Title :
A tight lower bound on the mutual information of a binary and an arbitrary finite random variable as a function of the variational distance
Author :
Stefani, Arno G. ; Huber, Johannes B. ; Jardin, Christophe ; Sticht, Heinrich
Author_Institution :
Inst. for Inf. Transm. (LIT) FAU Erlangen-Nuremberg Erlangen, Erlangen, Germany
Abstract :
In this paper a numerical method is presented, which finds a tight lower bound for the mutual information between a binary and an arbitrary finite random variable with joint distributions that have variational distance to a known joint distribution not greater than a known value. This lower bound can be applied to mutual information estimation with confidence intervals.
Keywords :
information theory; numerical analysis; statistical distributions; arbitrary finite random variable; binary finite random variable; confidence intervals; joint distributions; mutual information estimation; numerical method; tight lower bound; variational distance; Conferences; Joints; Minimization; Mutual information; Optimization; Probability distribution; Random variables;
Conference_Titel :
Communications Theory Workshop (AusCTW), 2014 Australian
Conference_Location :
Sydney, NSW
DOI :
10.1109/AusCTW.2014.6766418
