pyriemann.utils.kernel.kernel_logeuclid¶
- pyriemann.utils.kernel.kernel_logeuclid(X, Y=None, *, Cref=None, reg=1e-10)¶
Log-Euclidean kernel between two sets of SPD matrices.
Log-Euclidean kernel matrix \(\mathbf{K}\) of two sets \(\mathbf{X}\) and \(\mathbf{Y}\) of SPD matrices in \(\mathbb{R}^{n \times n}\) on tangent space at \(\mathbf{C}_\text{ref}\) is calculated with pairwise inner products [1]:
\[\mathbf{K}_{i,j} = \text{tr}( (\log(\mathbf{X}_i) - \log(\mathbf{C}_\text{ref})) (\log(\mathbf{Y}_j) - \log(\mathbf{C}_\text{ref})) )\]If \(\mathbf{C}_\text{ref}\) is None [2]:
\[\mathbf{K}_{i,j} = \text{tr}(\log(\mathbf{X}_i) \log(\mathbf{Y}_j))\]- Parameters:
- Xndarray, shape (n_matrices_X, n, n)
First set of SPD matrices.
- YNone | ndarray, shape (n_matrices_Y, n, n), default=None
Second set of SPD matrices. If None, Y is set to X.
- CrefNone | ndarray, shape (n, n), default=None
Reference SPD matrix. If None, Cref is defined as identity matrix.
Added in version 0.8.
- regfloat, default=1e-10
When Y is None, regularization parameter to mitigate numerical errors in kernel matrix estimation, to provide a positive-definite kernel matrix.
- Returns:
- Kndarray, shape (n_matrices_X, n_matrices_Y)
Log-Euclidean kernel matrix between X and Y.
See also
Notes
Added in version 0.3.
Changed in version 0.8: Add parameter Cref to use a reference matrix.
References
[1]A New Canonical Log-Euclidean Kernel for Symmetric Positive Definite Matrices for EEG Analysis G. L. W. vom Berg, V. Rohr, D. Platt and B. Blankertz. IEEE Transactions on Biomedical Engineering, 2024
[2]Factor analysis based spatial correlation modeling for speaker verification E. Wang, W. Guo, L. Dai, K. Lee, B. Ma and H. Li. IEEE ISCSLP, 2010