数字信号处理（卷积、幅频特性相频特性、零极点图、差分方程、各种序列的例题和代码）

import matplotlib.pyplot as plt import numpy as np from scipy import signal nmax=15 nmin=0 n=np.arange(nmin,nmax+1,1) def u(n): r=np.where(n>=0,1,0) return r num1=u(n) num2=n-1 y_shiyu=signal.convolve(num1,num2,mode='full',method='auto') #时域卷积 ws1,y_pinyu=signal.freqz(y_shiyu,whole=True) ws2,num1_pinyu=signal.freqz(num1,whole=True) ws3,num2_pinyu=signal.freqz(num2,whole=True) fupin1=20 * np.log10(abs(y_pinyu)) xiangpin1=np.angle(y_pinyu) fupin2=20 * np.log10(abs(num1_pinyu*num2_pinyu)) #频域相乘的幅频 xiangpin2=np.angle(num1_pinyu*num2_pinyu) plt.rcParams['font.sans-serif']=['SimHei'] plt.rcParams['axes.unicode_minus']=False plt.subplot(221) plt.plot(ws1,fupin1) plt.xlabel('ws') plt.ylabel('时域卷积幅频') plt.subplot(222) plt.plot(ws1,xiangpin1) plt.xlabel('ws') plt.ylabel('时域卷积相频') plt.subplot(223) plt.plot(ws2,fupin2) plt.xlabel('ws') plt.ylabel('频域相乘幅频') plt.subplot(224) plt.plot(ws2,xiangpin2) plt.xlabel('ws') plt.ylabel('频域相乘相频') plt.show()