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Laptop backup week 10? (for safety reasons)

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This commit is contained in:
Aidan Sharpe
2025-03-29 23:46:27 -04:00
parent 0f7490cb3e
commit 3ce102d959
30 changed files with 10785 additions and 8126 deletions
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22
8th-Semester-Spring-2025/clinic-consultant/labs/lab-3/lab3q3.py
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@@ -6,20 +6,32 @@ import matplotlib.pyplot as plt
def u(n):
return np.heaviside(n, 1)
# Transfer function for an ideal lowpass filter
def ideal_lowpass(omega, omega_c):
return np.where(np.abs(omega) <= omega_c, 1, 0)
def main():
omega_c = 0.4*np.pi
omega = np.arange(0, np.pi, 0.05*np.pi)
f_c = 0.4 # Cutoff frequency
omega_c = np.pi*f_c # Angular cutoff frequency
omega = np.arange(0, np.pi, 0.05*np.pi) # Frequency range
h_lpf = ideal_lowpass(omega, omega_c)
n = np.arange(-50, 51) # Sample range (100 samples centered at 0)
plt.plot(omega, h_lpf)
x = f_c*np.sinc(f_c*n) # Impulse resonse of ideal LPF
plt.stem(n,x)
plt.show()
h_lpf = ideal_lowpass(omega, omega_c) # Plot X(e^jw)
plt.plot(omega, h_lpf)
plt.xlabel("Frequency")
plt.ylabel("DTFT of Ideal Lowpass Filter")
for k in (10, 20, 30): # K values for truncated DTFT
w,h = sp.signal.freqz(x[50-k:50+k], 1, omega) # Calculate truncated DTFT
plt.plot(omega, np.abs(h)) # Plot magnitude of truncated DTFT
plt.show()
if __name__ == "__main__":
main()

5
8th-Semester-Spring-2025/clinic-consultant/labs/lab-3/lab3q5.m
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@@ -1,12 +1,17 @@
% First 100 samples
for n=0:99
y1(n+1) = (1 - (0.95)^(n+1))/0.05;
y2(n+1) = n + 1;
end
% Plot output of system for input x[n] = 0.95^n u[n]
figure(1)
n=0:1:99;
stem(n,y1)
xlabel('n')
ylabel('y(n)')
% Plot output of system for input x[n] = u[n]
figure(2)
n=0:1:99;
stem(n,y2)

23
8th-Semester-Spring-2025/clinic-consultant/labs/lab-3/lab3q5.py Normal file
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@@ -0,0 +1,23 @@
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
def main():
n = np.arange(100) # First 100 samples
y_1 = (1 - 0.95**(n+1))/0.05 # Output of system for input x[n] = 0.95^n u[n]
y_2 = n + 1 # Output of system for input x[n] = u[n]
plt.stem(n, y_1) # Plot y_1[n]
plt.xlabel("n")
plt.ylabel("y[n]")
plt.show()
plt.stem(n, y_2) # Plot y_2[n]
plt.xlabel("n")
plt.ylabel("y[n]")
plt.show()
if __name__ == "__main__":
main()