Abstract:
It is shown that the entropy of a sum of independent random vectors is a submodular set function, and upper bounds on the entropy of sums are obtained as a result in both...Show MoreMetadata
Abstract:
It is shown that the entropy of a sum of independent random vectors is a submodular set function, and upper bounds on the entropy of sums are obtained as a result in both discrete and continuous settings. These inequalities complement the lower bounds provided by the entropy power inequalities of Madiman and Barron (2007). As applications, new inequalities for the determinants of sums of positive-definite matrices are presented.
Published in: 2008 IEEE Information Theory Workshop
Date of Conference: 05-09 May 2008
Date Added to IEEE Xplore: 25 July 2008
ISBN Information: