# scipy.signal.kaiser_atten

scipy.signal.kaiser_atten(numtaps, width)

  Compute the attenuation of a Kaiser FIR filter.

  Given the number of taps N and the transition width width, compute the attenuation a in dB, given by Kaiser’s formula:

  > a = 2.285 * (N - 1) * pi * width + 7.95

  Parameters
    numtaps int

      The number of taps in the FIR filter.

    width float

      The desired width of the transition region between passband and stopband (or, in general, at any discontinuity) for the filter, expressed as a fraction of the Nyquist frequency.

  Returns
    a float

      The attenuation of the ripple, in dB.

  See also

  `kaiserord`, `kaiser_beta`

  Examples

  Suppose we want to design a FIR filter using the Kaiser window method that will have 211 taps and a transition width of 9 Hz for a signal that is sampled at 480 Hz. Expressed as a fraction of the Nyquist frequency, the width is 9/(0.5*480) = 0.0375. The approximate attenuation (in dB) is computed as follows:

      >>> from scipy.signal import kaiser_atten
      >>> kaiser_atten(211, 0.0375)
      64.48099630593983

scipy.signal.iirfilter scipy.signal.kaiser_beta