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How does thermal noise affect the time domain?
Thermal noise produces fluctuations about some average voltage that are Gaussian distributed in the time domain. These fluctuations in the time domain are shown in the image below.
What are the characteristics of a thermal noise?
Thermal noise is also known as white noise. It has the following characteristics: Fluctuations are Gaussian distributed in time. In other words, the size of a fluctuation between two points in time are Gaussian distributed. Fluctuations in time are uncorrelated.
Which is more useful time domain or frequency domain?
These time-domain signals are less useful than frequency-domain power spectra or power spectral densities. In particular, noise power spectral density (i.e., the power from random and deterministic EMI sources) can help you identify which EMI and noise sources in your design contribute to noise measured at specific points in space.
How to calculate the power spectral density of noise?
As long as the noise source follows a stationary process (i.e., time invariant), the power spectral density can be calculated with the following equation: The power spectral density S (f) is the discrete Fourier transform of the autocorrelation function R (k):
Why is noise a problem in optical systems?
Optical systems, communication systems, and other systems that require sensitive electronic and optical measurements can suffer from a variety of noise sources. The challenge in dealing with these noise sources is to identify them from time domain and/or frequency domain measurements.
What does the trace of 1 / f noise look like?
The trace of 1/f noise, in the time domain, looks a bit like the creeping of a worm, overlaid by noise. This ‘flickering’ trace named this kind of noise. In the frequency domain, its spectral density characteristic is a -1decade/decade slope in a log/log plot.