Python+Scipy доступны всегда, вместе с интернетом.
Welcome To Colaboratory - Colaboratory (google.com)
Можно поиграть и поквантовать коэффициенты так как надо
import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
fs = 1 # Sample rate, Hz
def plot_response(w, h, title):
"Utility function to plot response functions"
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(w, 20*np.log10(np.abs(h)))
ax.set_ylim(-80, 5)
ax.grid(True)
ax.set_xlabel('Frequency (Hz)')
ax.set_ylabel('Gain (dB)')
ax.set_title(title)
cutoff = 0.4 # Desired cutoff frequency
trans_width = 0.01/fs # Width of transition from pass to stop, Hz
numtaps = 256 # Size of the FIR filter.
taps = signal.remez(numtaps, [0, cutoff, cutoff + trans_width, 0.5*fs],
[1, 0], fs=fs)
w, h = signal.freqz(taps, [1], worN=2000, fs=fs)
plot_response(w, h, "Low-pass Filter")
plt.show()
