Multivariate Gaussian Mixture Model Optimization by Cross En

Version 1.3.0.0 (30 KB) by Sebastien PARIS
Stochastic multi-extremum optimization.
4.0
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10K Downloads
Updated 18 Feb 2020

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Fit a multivariate gaussian mixture by a cross-entropy method. Cross-Entropy is a powerfull tool to achieve stochastic multi-extremum optimization.

Please visit http://iew3.technion.ac.il/CE/ for more informations

i) Please compile mex-files by the mexme_ce_gauss.m (if compiler is not setup, run mex -setup before.

ii) Run the program demo test_ce_mvgm.m

Cite As

Sebastien PARIS (2024). Multivariate Gaussian Mixture Model Optimization by Cross En (https://www.mathworks.com/matlabcentral/fileexchange/7055-multivariate-gaussian-mixture-model-optimization-by-cross-en), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
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Version Published Release Notes
1.3.0.0

Fixed for modern Matlab & OS64
1.2.0.0

-Correct a problem with LCC compiler for dirirnd.c
-sample_mvgm.c compatible with GCC compiler
1.1.0.0

-Add mexme_ce_gauss.m to compile mex-files
1.0.0.0

v1.4 - Update randnt.c with a new uniform generator
- Improve help sections
- Change some fuction' names