Curious
Curious

Reputation: 276

Discrimination of clean signal and noisy signal in Python

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:

clean signal

noisy signal

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

Views: 31

Answers (0)

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