Information theoretical estimators toolbox. We present ITE (information theoretical estimators) a free and open source, multi-platform, Matlab/Octave toolbox that is capable of estimating many different variants of entropy, mutual information, divergence, association measures, cross quantities, and kernels on distributions. Thanks to its highly modular design, ITE supports additionally (i) the combinations of the estimation techniques, (ii) the easy construction and embedding of novel information theoretical estimators, and (iii) their immediate application in information theoretical optimization problems. ITE also includes a prototype application in a central problem class of signal processing, independent subspace analysis and its extensions.
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References in zbMATH (referenced in 5 articles , 1 standard article )
Showing results 1 to 5 of 5.
- Dias, Mafalda; Frazer, Jonathan; Westphal, Alexander: Inflation as an information bottleneck: a strategy for identifying universality classes and making robust predictions (2019)
- Karra, Kiran; Mili, Lamine: Copula index for detecting dependence and monotonicity between stochastic signals (2019)
- Grip, N.; Pfander, G. E.: Efficient analysis of OFDM channels (2017)
- Moussa, H.; Benallal, M. A.; Goyet, C.; Lefèvre, N.; El Jai, M. C.; Guglielmi, V.; Touratier, F.: A comparison of multiple non-linear regression and neural network techniques for sea surface salinity estimation in the tropical Atlantic Ocean based on satellite data (2015)
- Szabó, Zoltán: Information theoretical estimators toolbox (2014)