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MultitaperTfr

Namespace: RTPROCESSINGLIB  ·  Library: DSP Library

Python equivalent

mne.time_frequency.tfr_multitaper in MNE-Python.

#include <dsp/multitaper_tfr.h>

class UTILSLIB::MultitaperTfr

Sliding-window multitaper time-frequency representation.

Slides a fixed-length analysis window across the data and computes a multitaper PSD at each position, yielding a time-frequency power map per channel.

// 600 Hz data, 256-sample windows, 128-sample step, half-bandwidth 4
MultitaperTfrResult r = MultitaperTfr::compute(matData, 600.0);
// r.tfrData[ch] → n_freqs × n_time_steps

Static Methods​

compute(matData, sfreq, windowSize, stepSize, halfBandwidth, nTapers)​

Compute sliding-window multitaper TFR for every channel of a data matrix.

Parameters:

  • matData : const Eigen::MatrixXd & Data matrix (n_channels × n_times).

  • sfreq : double Sampling frequency in Hz.

  • windowSize : int Analysis window length in samples (default 256).

  • stepSize : int Step size in samples; -1 → windowSize / 2.

  • halfBandwidth : double Half-bandwidth parameter (NW); default 4.0.

  • nTapers : int Number of DPSS tapers; -1 → floor(2*halfBandwidth - 1).

Returns:

  • MultitaperTfrResult — MultitaperTfrResult with tfrData, vecFreqs, vecTimes.

Authors of this file​