Description Usage Arguments Details Value Author(s) References Examples
Cramer-Rao bound for the unmixing matrix estimate in the independent component model.
1 |
sdf |
a list of density functions of the sources scaled so that the mean is 0 and variance is 1. |
supp |
a two column matrix, where each row gives the lower and the upper limit used in numerical integration for the corresponding source component which is done using |
A |
the mixing matrix, identity by default. |
eps |
a value which is used when the derivative functions of the density functions are approximated. |
... |
arguments to be passed to |
Let \hat{W} denote an unmixing matrix estimate. If the estimate is affine equivariant, then the matrix \hat{G}=\hat{W}A does not depend on the mixing matrix A and the estimated independent components are \hat{S}=\hat{G}S, where S is the matrix of the true independent components.
A list containing the following components:
CRLB |
A matrix whose elements give the Cramer-Rao lower bounds for the asymptotic variances of the corresponding elements of \hat{G}. |
FIM |
The Fisher information matrix. |
EMD |
The sum of the Cramer-Rao lower bounds of the off-diagonal elements of \hat{G}. |
Jari Miettinen
Ollila, E., Kim, H. J. and Koivunen, V. (2008), Compact Cramer-Rao bound expression for independent component analysis. IEEE Transactions on Signal Processing, 56(4), 1421–1428.
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