pyriemann.utils.ajd.uwedge

pyriemann.utils.ajd.uwedge(X, *, init=None, eps=1e-07, n_iter_max=100)

Approximate joint diagonalization based on UWEDGE.

This is an implementation of the AJD algorithm [1] [2]: uniformly weighted exhaustive diagonalization using Gauss iterations (U-WEDGE). It is a translation from the Matlab code provided by the authors.

Parameters:

Xndarray, shape (n_matrices, n, n)

Set of symmetric matrices to diagonalize.

initNone | ndarray, shape (n, n), default=None

Initialization for the diagonalizer.

epsfloat, default=1e-7

Tolerance for stoping criterion.

n_iter_maxint, default=100

The maximum number of iterations to reach convergence.

Returns:

Vndarray, shape (n, n)

The diagonalizer.

Dndarray, shape (n_matrices, n, n)

Set of quasi diagonal matrices, D = V X V^T.

See also

ajd

Notes

New in version 0.2.4.

References

[1]

A Fast Approximate Joint Diagonalization Algorithm Using a Criterion with a Block Diagonal Weight Matrix P. Tichavsky, A. Yeredor and J. Nielsen. 2008 IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP.

[2]

Fast Approximate Joint Diagonalization Incorporating Weight Matrices P. Tichavsky and A. Yeredor. IEEE Trans Signal Process, 57(3), pp. 878 - 891, 2009.