Title :
Wyner´s common information in Gaussian channels
Author :
Pengfei Yang ; Biao Chen
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., Syracuse, NY, USA
fDate :
June 29 2014-July 4 2014
Abstract :
This paper considers the computation of Wyner´s common information between outputs of additive Gaussian channels with a common input. The work is motivated by recent generalization of Wyner´s common information to continuous random variables and the associated lossy source coding interpretation, as well as its application to statistical inference. It is shown that with independent and identically distributed Gaussian noises, Wyner´s common information between channel outputs is precisely the same as the mutual information between the source input and the channel outputs regardless of the source distribution. The result extends the previous result when the source distribution is Gaussian. Generalization to additive channels with correlated noises and its application to statistical estimation are also presented.
Keywords :
AWGN channels; estimation theory; source coding; statistical analysis; Wyner common information computation; additive Gaussian channels; associated lossy source coding interpretation; continuous random variables; correlated noises; identical distributed Gaussian noises; independent distributed Gaussian noises; statistical estimation; statistical inference; Additives; Bayes methods; Gaussian noise; Markov processes; Random variables; Source coding;
Conference_Titel :
Information Theory (ISIT), 2014 IEEE International Symposium on
Conference_Location :
Honolulu, HI
DOI :
10.1109/ISIT.2014.6875407