Fourier Transformation and Noise
I have learned Fourier transformation in maths classes, but i never know what is used for except decompose sin(x) and cos(x).
yesterday i knew Fourier Transformation can be used in Python to analyze noises. And there are many types of noises, which are differed by colors, white, blue and pink noises.
We did a Python code to plot White noise and Blue Noise.
Fourier transformation can decomposes a function of signal into frequencies,
Fourier Transform , then we can plot the frequencies in python phase_spectrum to detect the noise patterns and decide what methods we can reduce or filter some noise under special circumstances.
Noise data has systematic error and indeterminate(random) error.
Systematic error: error due to data collection procedures, miss read the scale. Those errors can be reduced.
Indeterminate(Random) error: statistical errors, such as Noise, which can not be reduced.
White Noise: Almost perfectly normal distributed around mean value, See below.
Blue Noise: Biased to higher noise.
Pink Noise: Decreased to lower noise. We can use Pink Noise to help sleep.
Interesting fact: if we have a huge spike around 60Hz; it is mostly due toElectric frequency.
Data used : voltage_3.
Detailed Code:Python voltage code
Thanks for Reading!