pyriemann.utils.ajd.rjd¶
- pyriemann.utils.ajd.rjd(X, *, init=None, eps=1e-08, n_iter_max=1000)¶
Approximate joint diagonalization based on Jacobi angles.
This is a direct implementation of the AJD algorithm by Cardoso and Souloumiac [1] used in JADE. The code is a translation of the Matlab code provided in the author website.
- Parameters:
- Xndarray, shape (n_matrices, n_channels, n_channels)
Set of symmetric matrices to diagonalize.
- initNone | ndarray, shape (n_channels, n_channels), default=None
Initialization for the diagonalizer.
- epsfloat, default=1e-8
Tolerance for stopping criterion.
- n_iter_maxint, default=1000
The maximum number of iterations to reach convergence.
- Returns:
- Vndarray, shape (n_channels, n_channels)
The diagonalizer, an orthogonal matrix.
- Dndarray, shape (n_matrices, n_channels, n_channels)
Set of quasi diagonal matrices.
Notes
New in version 0.2.4.
References
[1]Jacobi angles for simultaneous diagonalization J.-F. Cardoso and A. Souloumiac, SIAM Journal on Matrix Analysis and Applications, Volume 17, Issue 1, Jan. 1996.