pyssaBSS.jdc

Functions

joint_diagonalization(X[, weight, maxiter, eps])

Approximate joint diagonalization
pyssaBSS.jdc.joint_diagonalization(X, weight=None, maxiter=1000, eps=1e-06)[source]

Approximate joint diagonalization

Parameters:

  • X (ndarray of shape (kp, p)) – A concatenation of the k p-by-p matrices to be jointly diagonalized

  • weight (list(float), optional) – A list of weights given to each matrix, prior to diagonalization

  • maxiter (int) – maximum number of iteration in the algorithm before finishing. An assertion is raised if no convergence is found in this time.

  • eps (float) – convergence tolerance

Returns:

  • V (ndarray of shape (p, p)) – joint diagonalized

  • D (list of ndarrays of shape (p, p)) – Gives the “diagonalized” matrices from the procedure in a list

  • iter (int) – total number of iterations