
 Description:
ITE can estimate
entropy
: Shannon entropy, Rényi entropy, Tsallis entropy (Havrda and Charvát entropy), complex entropy, Phientropy (fentropy), SharmaMittal entropy,mutual information
: generalized variance, kernel canonical correlation analysis, kernel generalized variance, HilbertSchmidt independence criterion, Shannon mutual information (total correlation, multiinformation), L2 mutual information, Rényi mutual information, Tsallis mutual information, copulabased kernel dependency, multivariate version of Hoeffding's Phi, SchweizerWolff's sigma and kappa, complex mutual information, CauchySchwartz quadratic mutual information, Euclidean distance based quadratic mutual information, distance covariance, distance correlation, approximate correntropy independence measure, chisquare mutual information (HilbertSchmidt norm of the normalized crosscovariance operator, squaredloss mutual information, mean square contingency),divergence
: KullbackLeibler divergence (relative entropy, I directed divergence), L2 divergence, Rényi divergence, Tsallis divergence, Hellinger distance, Bhattacharyya distance, maximum mean discrepancy (kernel distance, an integral probability metric), Jdistance (symmetrised KullbackLeibler divergence, J divergence), CauchySchwartz divergence, Euclidean distance based divergence, energy distance (specially the CramerVon Mises distance), JensenShannon divergence, JensenRényi divergence, K divergence, L divergence, certain fdivergences (CsiszárMorimoto divergence, AliSilvey distance), nonsymmetric Bregman distance (Bregman divergence), JensenTsallis divergence, symmetric Bregman distance, Pearson chi square divergence (chi square distance),association measures
, includingmeasures of concordance
: multivariate extensions of Spearman's rho (Spearman's rank correlation coefficient, grade correlation coefficient), correntropy, centered correntropy, correntropy coefficient, correntropy induced metric, centered correntropy induced metric, multivariate extension of Blomqvist's beta (medial correlation coefficient), multivariate conditional version of Spearman's rho, lower/upper tail dependence via conditional Spearman's rho,cross quantities
: crossentropy,kernels on distributions
: expected kernel, Bhattacharyya kernel, probability product kernel, JensenShannon kernel, exponentiated JensenShannon kernel, JensenTsallis kernel, exponentiated JensenRenyi kernel(s), exponentiated JensenTsallis kernel(s),+some auxiliary quantities
: Bhattacharyya coefficient (Hellinger affinity).
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,
 multiplatform (tested extensively on Windows and Linux),
 free and open source (released under the GNU GPLv3(>=) license).
 Changes to previous version:
Entropy and KullbackLeibler divergence estimation based on power spectral density representation and Szegő's theorem: added.
Different noisy examples have been added to the image registration quick test.
 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, Measure Of Independence, Nonpa
 Archive: download here
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