pyriemann.utils.distance.distance_kullback_sym¶

pyriemann.utils.distance.distance_kullback_sym(A, B, squared=False)¶

Symmetrized Kullback-Leibler divergence between SPD/HPD matrices.

The symmetrized Kullback-Leibler divergence between two SPD/HPD matrices \(\mathbf{A}\) and \(\mathbf{B}\) is the sum of left and right Kullback-Leibler divergences. It is also called Jeffreys divergence [1].

Parameters:

Andarray, shape (…, n, n): First SPD/HPD matrices, at least 2D ndarray.
Bndarray, shape (…, n, n): Second SPD/HPD matrices, same dimensions as A.
squaredbool, default False: Return squared distance.

New in version 0.5.

Returns:

dfloat or ndarray, shape (…,): Symmetrized Kullback-Leibler divergence between A and B.