File:Periodogram windows.png
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The linear spectrum calculated by the periodogram method (rectangular and Hamming window functions).
Summary
editDescriptionPeriodogram windows.png |
English: Developed using scipy.signal.periodogram. |
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Date | ||||
Source | Own work | |||
Author | Kirlf | |||
Other versions |
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PNG development InfoField | ![]() This plot was created with Matplotlib. | |||
Source code InfoField | Python codeimport numpy as np
from scipy import signal
import matplotlib.pyplot as plt
w_1 = 40 # frequency of the 1st component of the signal (Hz)
w_2 = 60 # frequency of the 2nd component of the signal (Hz)
a = 0.5 # magnitude of the 1st component of the signal
b = 1.0 # magnitude of the 2nd component of the signal
t = np.array([i for i in range(1,301)])/1000 # time samples (s)
fs = 1 / (t[1]-t[0]) # sampling frequency (Hz)
x = a*np.cos(2*np.pi*w_1*t) + b*np.sin(2*np.pi*w_2*t) # considered signal
n = .2*np.random.randn(len(t)) # white Gaussian noise
y = x + n
windows = [None,'hamming']
plt.subplots(1, 1, figsize=(6, 4), dpi=250)
for window in windows:
if window == None:
label = 'rect'
else:
label = window
f, Pxx_den = signal.periodogram(y, fs=fs, scaling='spectrum', nfft=2048, window=window)
plt.semilogy(f[1:200], Pxx_den[1:200], label=label)
plt.subplots(1, 1, figsize=(6, 4), dpi=250)
plt.ylabel('Spectrum')
plt.xlabel('Frequencies (Hz)')
plt.title('Periodogram')
plt.grid(True)
plt.show()
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Date/Time | Thumbnail | Dimensions | User | Comment | |
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current | 06:22, 20 February 2019 | ![]() | 1,500 × 1,000 (154 KB) | Kirlf (talk | contribs) | User created page with UploadWizard |
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