Title :
Total variation distance and the distribution of relative information
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., Princeton, NJ, USA
Abstract :
We give explicit expressions, upper and lower bounds on the total variation distance between P and Q in terms of the distribution of the random variables log dP/dQ (X) and log dP/dQ(Y), where X and Y are distributed accorκding to P and Q respectively.
Keywords :
information theory; random processes; lower bound; random variables; relative information distribution; total variation distance; upper bound; Entropy; Information theory; Q measurement; Random variables; US Government; Upper bound;
Conference_Titel :
Information Theory and Applications Workshop (ITA), 2014
Conference_Location :
San Diego, CA
DOI :
10.1109/ITA.2014.6804281
