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InvMxne

Namespace: INVERSELIB  ·  Library: Inverse Library

Python equivalent

mne.inverse_sparse.mixed_norm in MNE-Python.

#include <inv/inv_mxne.h>

class INVLIB::InvMxne

Mixed-Norm Estimate (MxNE) sparse inverse solver.

Minimizes: ||M - G*X||^2_F + alpha * sum_i ||X_i||_2 using an Iteratively Reweighted Least Squares (IRLS) approach for the L21-norm (group lasso).

MxNE sparse inverse solver.

Static Methods​

compute(matGain, matData, alpha, nIterations, tolerance)​

Compute the MxNE inverse solution.

Parameters:

  • matGain : const Eigen::MatrixXd & Forward gain matrix (n_channels x n_sources).

  • matData : const Eigen::MatrixXd & Measurement data (n_channels x n_times).

  • alpha : double Regularization parameter.

  • nIterations : int Maximum number of IRLS iterations.

  • tolerance : double Convergence tolerance on weight change.

Returns:

  • InvMxneResult — The MxNE result containing the sparse source estimate.

Authors of this file​