Title :
A variational perspective over an extremal entropy inequality
Author :
Park, Soojin ; Serpedin, Erchin ; Qaraqe, Marwa
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
This paper proposes a novel variational approach for proving the extremal entropy inequality (EEI) [1]. Unlike previous proofs [1], [2], the proposed variational approach is simpler and it does not require neither the classical entropy power inequality (EPI) [1], [2] nor the channel enhancement technique [1]. The proposed approach is versatile and can be easily adapted to numerous other applications such as proving or extending other fundamental information theoretic inequalities such as the EPI, worst additive noise lemma, and Cramér-Rao inequality.
Keywords :
entropy; variational techniques; Cramer-Rao inequality; EEI; EPI; entropy power inequality; extremal entropy inequality; fundamental information theoretic inequalities; proving; variational approach; variational perspective; worst additive noise lemma; Additive noise; Calculus; Covariance matrices; Entropy; Equations; Information theory; Vectors;
Conference_Titel :
Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on
Conference_Location :
Istanbul
DOI :
10.1109/ISIT.2013.6620297