Margenau-Hill Representation of Chirps with Different Slopes

This example demonstrates the Margenau-Hill distribution of a signal composed of two chirps with Gaussian amplitude modulation but havind linear frequency modulations with different slopes. This distribution too, like the Wigner-Ville distribution, spearates the signal terms, but produces interferences such that they appear diagonally opposite their corresponding signals.

Figure 4.14 from the tutorial.

import numpy as np
from tftb.generators import atoms
from tftb.processing import MargenauHillDistribution


sig = atoms(128, np.array([[32, 0.15, 20, 1], [96, 0.32, 20, 1]]))
tfr = MargenauHillDistribution(sig)
tfr.run()
tfr.plot(show_tf=True, kind='contour', sqmod=False, threshold=0,
         contour_y=np.linspace(0, 0.5, tfr.tfr.shape[0] / 2))