In this tutorial, we will use some examples to show you how to use numpy.hamming() functions.
numpy.hamming() function is defined as:
It can create a hamming window.
How to compute hamming window?
Hamming window is calculated as follows:
Here is an image for hamming window when M = 51
How to use numpy.hamming()?
Here is an example:
import numpy as np win = np.hamming(12) print(win)
Run this codoe, you will get:
[0.08 0.15302337 0.34890909 0.60546483 0.84123594 0.98136677 0.98136677 0.84123594 0.60546483 0.34890909 0.15302337 0.08 ]
In audio processing, we often add use hamming window to the frame to reduce signal discontinuity at the beginning and end of the frame.