torch.signal.windows.kaiser
torch.signal.windows.kaiser(M, *, beta=12.0, sym=True, dtype=None, layout=torch.strided, device=None, requires_grad=False)
Computes the Kaiser window.
The Kaiser window is defined as follows:
  w_n = I_0 \left( \beta \sqrt{1 - \left( {\frac{n - N/2}{N/2}}
  \right) ^2 } \right) / I_0( \beta )

where "I_0" is the zeroth order modified Bessel function of the
   first kind (see "torch.special.i0()"), and "N = M - 1 if sym else
   M".
The window is normalized to 1 (maximum value is 1). However, the 1
   doesn't appear if "M" is even and "sym" is True.
Parameters:
      M (int) -- the length of the window. In other words, the
      number of points of the returned window.
Keyword Arguments:
      * beta (float, optional) -- shape parameter for the
        window. Must be non-negative. Default: 12.0
  * **sym** (*bool**, **optional*) -- If *False*, returns a
