mode_dist: EM Baggenstoss: mode_dist

In Mthrun/AdaptGauss2D: Gaussian Mixture Modeling in 2D

EM Baggenstoss: mode_dist

Description

Distance (actually closeness) measure between 2 modes with means m1, m2 and cholesky covariance matrices v1, v2. Returns negative closeness measure (for identical modes, d = 0).

Usage

mode_dist(Mean1, Mean2, Covariance1, Covariance2)

Arguments

Mean1	Numerical vector with mean of first mode (d-dimensional where d denotes the features dimension).
Mean2	Numerical vector with mean of second mode (d-dimensional where d denotes the features dimension).
Covariance1	Numerical matrix with covariance matrix of first mode (dxd matrix where d denotes the feature's dimension).
Covariance2	Numerical matrix with covariance matrix of second mode (dxd matrix where d denotes the feature's dimension).

Value

List with one element:

Dist	Numerical value with distance of two modes.

Author(s)

Quirin Stier

References

Baggenstoss, Paul M., and T. E. Luginbuhl.: An EM algorithm for joint model estimation. IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), Phoenix, AZ, USA, 1999, pp. 1825-1828 vol.4, IEEE, doi:10.1109/ICASSP.1999.758276, 1999.

Mthrun/AdaptGauss2D documentation built on July 19, 2022, 3:11 a.m.