#include <MI.hh>
Public Methods | |
MI () | |
virtual | ~MI () |
void | Allocate (int nb_dimensions) |
Memory allocation. More... | |
void | Initialise1 (vector< float ** > *C1, vector< float * > *M1) |
Initialize variable at T1 and calculates the covariance matrix determinant. More... | |
void | Initialise2 (vector< float ** > *C2, vector< float * > *M2) |
Initialize variable at T2 and calculates the covariance matrix determinant. More... | |
void | Initialise12 (vector< float ** > *C12, vector< float * > *M12) |
Initialize variable at T12 and calculates the covariance matrix determinant. More... | |
float | MICalculus () |
Mutual information calculation. More... | |
Private Methods | |
void | DetCovMatrixT1 () |
determinant calculation at T1. More... | |
void | DetCovMatrixT2 () |
determinant calculation at T2. More... | |
void | DetCovMatrixT12 () |
determinant calculation at T12. More... | |
Private Attributes | |
vector< float * > | MeanT1 |
mean vector time 1. | |
vector< float * > | MeanT2 |
mean vector time 2. | |
vector< float * > | MeanT12 |
mean vector time 1 and 2. | |
vector< float ** > | CovT1 |
covariance matrix time 1. | |
vector< float ** > | CovT2 |
covariance matrix time 2. | |
vector< float ** > | CovT12 |
covariance matrix time 1 and 2. | |
vector< float > | determinantT1 |
Determinant covariance matrix time 1. | |
vector< float > | determinantT2 |
Determinant covariance matrix time 2. | |
vector< float > | determinantT12 |
Determinant covariance matrix time 1 and 2. | |
int | nb_dim |
dimensionnality. |
The procedure is based on the determinants of covaraint matrices corresponding to the 2 Gaussian distributions (T1 and T2) and to the joint distribution T12
Definition at line 14 of file MI.hh.
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Memory allocation. This method should be simpler. Indeed, the vector objects used here could be replace by a simple scalar.
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determinant calculation at T1. method based on a LU decomposition provided by Numerical recepies Note that when the matrix is singular the determinants is calculated with a covariance matrix where the singular dimensions have been removed. |
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determinant calculation at T12. method based on a LU decomposition provided by Numerical recepies Note that when the matrix is singular the determinants is calculated with a covariance matrix where the singular dimensions have been removed. |
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determinant calculation at T2. method based on a LU decomposition provided by Numerical recepies Note that when the matrix is singular the determinants is calculated with a covariance matrix where the singular dimensions have been removed. |
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Initialize variable at T1 and calculates the covariance matrix determinant.
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Initialize variable at T12 and calculates the covariance matrix determinant.
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Initialize variable at T2 and calculates the covariance matrix determinant.
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Mutual information calculation. This function computes a simple ration of determinants for the mutual information calculation. Note that if there are singular covariance matrices, the mutual information is still equal to the ratio of determinants, but the singular dimensions must be removed from the marginal and joint covariance matrices.
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