Pretty much all of Fall 2024

7th-Semester-Fall-2024/ECOMMS/labs/lab1/part1.py

@@ -1,5 +1,5 @@
 import numpy as np
-import sounddevice as sd
+#import sounddevice as sd
 import matplotlib.pyplot as plt
 
 def normalize_signal(signal):
@@ -10,12 +10,37 @@ def normalize_signal(signal):
     normalized_signal -= 1
     return normalized_signal
 
-snr = 10
-
 f = 466.16
 f_s = 16000
+T_0 = 1/f
 
-t = np.arange(0,0.01,1/f_s)
+t = np.arange(0,T_0,1/f_s)
 s = 0.5 * np.sin(2*np.pi*f*t)
 
-sd.play(normalize_signal(s), samplerate=f_s, blocking=True)
+# Convert signal covariance
+var_s = np.cov(s)
+
+# Calculate required noise variance
+var_snr_10 = var_s/(10**(10/10))
+var_snr_20 = var_s/(10**(20/10))
+var_snr_30 = var_s/(10**(30/10))
+
+# Genearate noise
+noise_snr_10 = (var_snr_10**0.5) * np.random.randn(len(s))
+noise_snr_20 = (var_snr_20**0.5) * np.random.randn(len(s))
+noise_snr_30 = (var_snr_30**0.5) * np.random.randn(len(s))
+
+# Add signal and noise
+m_snr_10 = s+noise_snr_10
+m_snr_20 = s+noise_snr_20
+m_snr_30 = s+noise_snr_30
+
+plt.plot(t,s, label="Pure A$\sharp$ Tone")
+plt.plot(t,m_snr_10, label="Corrupted A$\sharp$ Tone (SNR=10dB)")
+plt.plot(t,m_snr_20, label="Corrupted A$\sharp$ Tone (SNR=20dB)")
+plt.plot(t,m_snr_30, label="Corrupted A$\sharp$ Tone (SNR=30dB)")
+plt.legend()
+plt.title("Pure and Corrupted A$\sharp$ Tones")
+plt.xlabel("Time (s)")
+plt.show()
+#sd.play(normalize_signal(s), samplerate=f_s, blocking=True)

7th-Semester-Fall-2024/ECOMMS/labs/lab1/part2.py

@@ -0,0 +1,33 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import scipy as sp
+
+f_s = 8E3
+
+T_s = 1/f_s
+t = np.arange(-5,5,T_s)
+
+f = np.linspace(0,f_s,len(t))
+omega = 2*np.pi*f
+
+def u(t):
+    return np.heaviside(t, 1)
+
+w = u(t) - u(t-0.6) + u(t-0.7) - u(t-1)
+
+W_c = 1j*(np.exp(-1j*omega*0.6) + np.exp(-1j*omega) - np.exp(-1j*omega*0.7) - 1)/omega
+W_d = sp.fft.fft(w)
+
+print(W_c[:10])
+print(W_d[:10])
+
+
+plt.plot(t,w)
+plt.show()
+
+
+plt.subplot(211)
+plt.plot(W_c)
+plt.subplot(212)
+plt.plot(W_d)
+plt.show()

7th-Semester-Fall-2024/ECOMMS/labs/lab1/part3.py

@@ -0,0 +1,54 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import scipy as sp
+
+f_m = 5E3
+f_c = 25E3
+
+f_s = 50*f_c
+
+T_m = 1/f_m
+T_c = 1/f_c
+T_s = 1/f_s
+
+A_c = 10
+A_m = 1
+
+t = np.arange(0,2*T_m,T_s)
+f = t*f_s/(2*T_m)
+
+# ===== AM =====
+s = A_c * (1 + A_m*np.cos(2*np.pi*f_m*t)) * np.cos(2*np.pi*f_c*t)
+
+var_s = np.cov(s)
+
+SNR = 10
+var_snr = var_s/(10**(SNR/10))
+noise_snr = (var_snr**0.5) * np.random.randn(len(s))
+m = s+noise_snr
+
+S = sp.fft.fft(s)
+M = sp.fft.fft(m)
+
+plt.subplot(211)
+plt.stem(f, S)
+plt.subplot(212)
+plt.stem(f, M)
+plt.show()
+
+# ===== FM =====
+beta_f = 10
+s = A_c*np.cos(2*np.pi*f_c*t + beta_f*A_m*np.sin(2*np.pi*f_m*t))
+
+var_snr = var_s/(10**(SNR/10))
+noise_snr = (var_snr**0.5) * np.random.randn(len(s))
+m = s+noise_snr
+
+S = sp.fft.fft(s)
+M = sp.fft.fft(m)
+
+plt.subplot(211)
+plt.stem(f, S)
+plt.subplot(212)
+plt.stem(f, M)
+plt.show()