spkit.minMSE

spkit.minMSE(x, y, W=5, show=False)

Minimum Mean Squared Error under temporal shift

for t = -W to W

\[minMSE = min \{ 1/K \sum_0^K-1 ( (x(k) - y(k-t))**2 ) \}\]

Parameters:

Returns:

See also

spkit

#TODO

Notes

#TODO

References

• wikipedia -

Examples

>>> import numpy as np
>>> import spkit as sp
>>> #TODO