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This is also derived from $$\frac{\sigma_W+\mu_W^2}{\mu_W^2} \tag{8}$$

Where $\sigma_W$ is the variance of the window and $\mu_W$ is the mean of the window.

ENBW and PG are useful metrics when comparing window functions.

ENBW and PG are useful metrics when comparing window functions.

Update: I just saw this related article posted on Linked-In, I only read it over quickly but appears to be much more detailed and relevant to this post so will link here: https://www.gaussianwaves.com/2020/09/equivalent-noise-bandwidth-enbw-of-window-functions/

BOTTOM LINE

SUMMARY