Estimation of Mutual Information

This book presents the mutual information (MI) estimation methods recently proposed by the author and published in a number of major journals. It includes two types of applications: learning a forest structure from data for multivariate variables and identifying independent variables (independent component analysis). MI between a pair of random variables is mathematically defined in information theory. It measures how dependent the two variables are, takes nonnegative values, and is zero if...