Use python to implement digital filter (FIR)

Use python to implement digital filter (FIR)

import scipy.signal as signalimport numpy as npimport pylab as plimport matplotlib.pyplot as pltimport matplotlib

Set filter parameters and create Signals

# A = np. array ([1.0,-1.947463016918843, 0.9555873701383931]) B = np. array ([0.9833716591860479,-1.947463016918843, 0.9722157109523452]) #44.1 kHz, 1 second frequency scanning wave t = np. arange (0, 0.5, 1/44100. 0) x = signal. chirp (t, f0 = 10, t1 = 0.5, f1 = 1000.0) # output of the directly one-time computing filter y = signal. lfilter (B, a, x) plt. plot (x) plt. show ()

# Divide the input signal into 50 data sets x2 = x. reshape (-) # The initial state of the filter is 0, and the length is the length of the filter coefficient-1z = np. zeros (max (len (a), len (B)-1, dtype = np. float) y2 = [] # Save the output list for tx in x2: # filter each signal segment and update the filter status z ty, z = signal. lfilter (B, a, tx, zi = z) # Add the output to the output List B y2.append (ty) # convert the output y2 to a one-dimensional array y2 = np. array (y2) y2 = y2.reshape (-1,) # print np. sum (y-y2) ** 2) # plot pl. plot (t, y, t, y2) pl. show ()