Description:

ITE can estimate

• entropy: Shannon entropy, Rényi entropy, Tsallis entropy (Havrda and Charvát entropy), complex entropy,

• mutual information: generalized variance, kernel canonical correlation analysis, kernel generalized variance, Hilbert-Schmidt independence criterion, Shannon mutual information, L2 mutual information, Rényi mutual information, Tsallis mutual information, copula-based kernel dependency, multivariate version of Hoeffding's Phi, complex mutual information, Cauchy-Schwartz quadratic mutual information, Euclidean distance based quadratic mutual information,

• divergence: Kullback-Leibler divergence (relative entropy), L2 divergence, Rényi divergence, Tsallis divergence, Hellinger distance, Bhattacharyya distance, maximum mean discrepancy (kernel distance), J-distance (symmetrised Kullback-Leibler divergence), Cauchy-Schwartz divergence, Euclidean distance based divergence,

• association measures, including measures of concordance: multivariate extensions of Spearman's rho (Spearman's rank correlation coefficient, grade correlation coefficient),

• cross quantities: cross-entropy.

ITE offers solution methods for

• Independent Subspace Analysis (ISA) and
• its extensions to different linear-, controlled-, post nonlinear-, complex valued-, partially observed models, as well as to systems with nonparametric source dynamics.

ITE is

• written in Matlab/Octave,
• multi-platform (tested extensively on Windows and Linux),
• free and open source (released under the GNU GPLv3(>=) license).

Changes to previous version:

MMD (maximum mean discrepancy) estimation based on U- and V-statistics: added.

BibTeX Entry: Download

Corresponding Paper BibTeX Entry: Download

Supported Operating Systems: Linux, Windows

Data Formats: Matlab, Octave

Tags: Entropy, Mutual Information, Divergence, Independent Subspace Analysis, Separation Principles, Independent Process Analysis, Association Measure, Measure Of Concordance

Archive: download here

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