KL divergence between two multivariate Gaussians
This function computes the Kullback-Leibler (KL) divergence between two multivariate Gaussian distributions with specified parameters (mean and covariance matrix). The covariance matrices must be positive definite. The code is efficient and numerically stable.
Examples:
1) Compute the KL divergence between two univariate Gaussians: KL( N(-1,1) || N(+1,1) )
mu1 = -1; mu = +1;
s1 = 1; s2 = 1;
mvgkl(mu1, s1^2, mu2, s2^2)
2) Compute the KL divergence between two bivariate Gaussians: KL( N(mu1,S1) || N(mu2,S2) )
mu1 = [-1 -1]'; mu2 = [+1, +1]';
S1 = [1 0.5; 0.5 1]; S2 = [1 -0.7; -0.7 1];
mvgkl(mu1, S1, mu2, S2)
Zitieren als
Statovic (2024). KL divergence between two multivariate Gaussians (https://www.mathworks.com/matlabcentral/fileexchange/87899-kl-divergence-between-two-multivariate-gaussians), MATLAB Central File Exchange. Abgerufen .
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Version | Veröffentlicht | Versionshinweise | |
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1.0.2 | -minor edits; title slightly changed |
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1.0.1 | -minor description edits |
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1.0.0 |