Filtering is a type of signal processing, which involves removing or suppressing a part of the signal. After applying FFT, we can filter high or low frequencies, or we can try to remove the white noise. White noise is a random signal with a constant power spectrum and as such doesn't contain any useful information. The scipy.signal package has a number of utilities for filtering. In this example, we will demonstrate a small sample of these routines:
The median filter calculates the median in a rolling window (see http://en.wikipedia.org/wiki/Median_filter). It's implemented by the
medfilt()function, which has an optional window size parameter.The Wiener filter removes noise using statistics (see http://en.wikipedia.org/wiki/Wiener_filter). For a filter
g(t)and signals(t), the output is calculated with the convolution(g * [s + n])(t). It's implemented by thewiener()function. This function also has an optional window size parameter.