TY - GEN
T1 - A variational perspective over an extremal entropy inequality
AU - Park, Sangwoo
AU - Serpedin, Erchin
AU - Qaraqe, Marwa
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84890381287&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2013.6620297
DO - 10.1109/ISIT.2013.6620297
M3 - Conference contribution
AN - SCOPUS:84890381287
SN - 9781479904464
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 604
EP - 608
BT - 2013 IEEE International Symposium on Information Theory, ISIT 2013
T2 - 2013 IEEE International Symposium on Information Theory, ISIT 2013
Y2 - 7 July 2013 through 12 July 2013
ER -