spkit
.mean_minSE¶
- spkit.mean_minSE(x, y, W=5, show=False, compare_mse=True, plot_log=False, esp=0.001, show_legend=True)¶
Mean of Minimum Squared Error (MMSE) under temporal shift
Mean of Minimum Squared Error (MMSE) is the metric computed the closeness of two signals. MMSE ignores the a little
for t = -W to W
\[MminSE = 1/K \sum_0^K-1 min( (x(k) - y(k-t))**2 ) \]- Parameters:
- x: 1d-array
- y: 1d-array
- Returns:
See also
spkit
#TODO
Notes
#TODO
References
wikipedia -
Examples
>>> import numpy as np >>> import spkit as sp >>> #TODO