DocumentCode :
40863
Title :
Mutual Information Matrices Are Not Always Positive Semidefinite
Author :
Jakobsen, Sune K.
Author_Institution :
Sch. of Math. Sci., Queen Mary Univ. of London, London, UK
Volume :
60
Issue :
5
fYear :
2014
fDate :
May-14
Firstpage :
2694
Lastpage :
2696
Abstract :
For discrete random variables X1, ..., Xn we construct an n by n matrix. In the (i, j)-entry we put the mutual information I(Xi ; Xj) between Xi and Xj. In particular, in the (i, i)-entry we put the entropy H(Xi) = I(Xi; Xi) of Xi. This matrix, called the mutual information matrix of (X1, ..., Xn), has been conjectured to be positive semidefinite. In this paper, we give counterexamples to the conjecture, and show that the conjecture holds for up to three random variables.
Keywords :
entropy; matrix algebra; discrete random variables; entropy; mutual information matrix; Computer science; Educational institutions; Eigenvalues and eigenfunctions; Entropy; Linear matrix inequalities; Mutual information; Random variables; Information inequalities; linear algebra; mutual information;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2014.2311434
Filename :
6774945
Link To Document :
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