INVLIB::InvTfMxne Class Reference

Time-Frequency Mixed-Norm Estimate (TF-MxNE) sparse inverse solver. More...

#include <inv_tf_mxne.h>

Static Public Member Functions
static InvTfMxneResult	compute (const Eigen::MatrixXd &matGain, const Eigen::MatrixXd &matData, const InvTfMxneParams &params=InvTfMxneParams())
	Compute the TF-MxNE inverse solution.
static Eigen::MatrixXd	buildGaborDictionary (int iNSamples, int iNFreqs, double dFMin, double dFMax, double dSFreq)
	Build a Gabor dictionary (tight frame) for time-frequency decomposition.

Detailed Description

Time-Frequency Mixed-Norm Estimate (TF-MxNE) sparse inverse solver.

Solves the inverse problem in the time-frequency domain: min ||M - G*Phi*Z||^2_F + alpha_space * ||Z||_21 + alpha_time * ||Z||_1

where Phi is a Gabor dictionary (tight frame) and Z are the TF coefficients. The L21 penalty enforces spatial sparsity (few active sources) while L1 enforces temporal sparsity (focal activations in time-frequency).

Usage:

InvTfMxneParams params;
params.dAlphaSpace = 0.5;
params.dAlphaTime  = 0.1;
params.dSFreq      = 1000.0;
InvTfMxneResult result = InvTfMxne::compute(matGain, matData, params);

Definition at line 108 of file inv_tf_mxne.h.

Member Function Documentation

buildGaborDictionary()

MatrixXd InvTfMxne::buildGaborDictionary ( int iNSamples, int iNFreqs, double dFMin, double dFMax, double dSFreq )

static

Build a Gabor dictionary (tight frame) for time-frequency decomposition.

Parameters

[in]	iNSamples	Number of time samples.
[in]	iNFreqs	Number of frequency bins.
[in]	dFMin	Minimum frequency (Hz).
[in]	dFMax	Maximum frequency (Hz).
[in]	dSFreq	Sampling frequency (Hz).

Returns

Gabor dictionary matrix (n_atoms × n_samples), where n_atoms = n_freqs * n_samples.

Definition at line 45 of file inv_tf_mxne.cpp.

compute()

InvTfMxneResult InvTfMxne::compute ( const Eigen::MatrixXd & matGain, const Eigen::MatrixXd & matData, const InvTfMxneParams & params = InvTfMxneParams() )

static

Compute the TF-MxNE inverse solution.

Parameters

[in]	matGain	Forward gain matrix (n_channels × n_sources).
[in]	matData	Measurement data (n_channels × n_times).
[in]	params	TF-MxNE parameters.

Returns

TF-MxNE result with sparse source estimate.

Definition at line 95 of file inv_tf_mxne.cpp.

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The documentation for this class was generated from the following files:

• src/libraries/inv/sparse/inv_tf_mxne.h
• src/libraries/inv/sparse/inv_tf_mxne.cpp