Reputation: 276
I have the following SNR signals:
import numpy as np
import matplotlib.pyplot as plt
SNR_signal = np.array([0.10134662, 0.00941053, 0.15660532, 0.30411626, 0.59214933,
0.90592892, 1.21066261, 1.68196251, 1.9605259 , 2.34029174,
2.65199842, 3.01118228, 3.16316174, 3.28022538, 3.34901719,
3.21725934, 3.3490386 , 3.20125906, 2.92811981, 2.89281209,
2.46155156, 2.13995433, 1.90885968])
SNR_signal_noisy = np.array([-0.40453594, 0.23530384, -0.2138662 , 0.78094685,
2.21687829, 1.59897599, 1.97371773, 2.30516968, 1.23779907, 1.64628358,
4.99010801, 2.72729907, 3.45409474, 3.0851324 , 1.89160872,
3.84695234, 1.74147151, 3.20327341, 4.00223569, 1.87373223,
2.65093098, 1.55633982, 2.05920386])
plt.plot(SNR_signal)
plt.show()
plt.plot(SNR_signal_noisy)
plt.show()
with their plots:
and I'd like to estimate the level of noise between these signals. I tried psd method, but it didn't work well.
What is the best way to estimate the noise level in these signals?
Upvotes: 0
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