منابع مشابه
On Classification of Bivariate Distributions Based on Mutual Information
Among all measures of independence between random variables, mutual information is the only one that is based on information theory. Mutual information takes into account of all kinds of dependencies between variables, i.e., both the linear and non-linear dependencies. In this paper we have classified some well-known bivariate distributions into two classes of distributions based on their mutua...
متن کاملLower bounds on mutual information.
We correct claims about lower bounds on mutual information (MI) between real-valued random variables made by Kraskov et al., Phys. Rev. E 69, 066138 (2004). We show that non-trivial lower bounds on MI in terms of linear correlations depend on the marginal (single variable) distributions. This is so in spite of the invariance of MI under reparametrizations, because linear correlations are not in...
متن کاملClustering of a Number of Genes Affecting in Milk Production using Information Theory and Mutual Information
Information theory is a branch of mathematics. Information theory is used in genetic and bioinformatics analyses and can be used for many analyses related to the biological structures and sequences. Bio-computational grouping of genes facilitates genetic analysis, sequencing and structural-based analyses. In this study, after retrieving gene and exon DNA sequences affecting milk yield in dairy ...
متن کاملA Review on Multivariate Mutual Information
Typically, mutual information is defined and studied between just two variables. Though the approach to evaluate bivariate mutual information is well established, several problems in multi-user information theory require the knowledge of interaction between more than two variables. Since there exists dependency between the variables, we cannot decipher their relationship without considering all...
متن کاملOn the Distribution of Mutual Information
In the early years of information theory, mutual information was defined as a random variable, and error probability bounds for communication systems were obtained in terms of its probability distribution. We advocate a return to this perspective for a renewed look at information theory for general channel models and finite coding blocklengths. For capacityachieving inputs, we characterize the ...
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ژورنال
عنوان ژورنال: Advances in Applied Mathematics
سال: 1995
ISSN: 0196-8858
DOI: 10.1006/aama.1995.1013