File:Periodogram.png

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Summary

Description
English: Developed using scipy.signal.periodogram.
Date
Source Own work
Author Kirlf
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This plot was created with Matplotlib
Source code
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Python code

import numpy as np
from scipy import signal
import matplotlib.pyplot as plt

w_1 = 30 # frequency of the 1st component of the signal (Hz)
w_2 = 50 # frequency of the 2nd component of the signal (Hz)

a = 1.1 # magnitude of the 1st component of the signal
b = 0.6 # 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
f, Pxx_den = signal.periodogram(x, fs=fs, scaling='spectrum')

plt.subplots(1, 1, figsize=(6, 4), dpi=250)
plt.stem(f[:50], Pxx_den[:50], '-')
plt.ylabel('Spectrum')
plt.xlabel('Frequencies (Hz)')
plt.title('Periodogram')
plt.grid(True)
plt.show()

Licensing

I, the copyright holder of this work, hereby publish it under the following licence:
w:en:Creative Commons
attribution share alike
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International licence.
You are free:
  • to share – to copy, distribute and transmit the work
  • to remix – to adapt the work
Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the licence, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible licence as the original.

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The linear spectrum calculated by the periodogram method.

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20 February 2019

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current10:51, 20 February 2019Thumbnail for version as of 10:51, 20 February 20191,500 × 1,000 (50 KB)wikimediacommons>KirlfUser created page with UploadWizard

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