Oh, dude, Gaussian kernels are used in wavelet transforms because they have a smooth and bell-shaped curve that helps in capturing both low and high-frequency components of a signal. It's like they're the cool kids at the party who can mingle with everyone. So, when we want to analyze signals with varying frequencies, we invite Gaussian kernels to the wavelet transform shindig because they know how to handle the crowd.
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The Gaussian distribution is the same as the normal distribution. Sometimes, "Gaussian" is used as in "Gaussian noise" and "Gaussian process." See related links, Interesting that Gauss did not first derive this distribution. That honor goes to de Moivre in 1773.
Gaussian elimination is used to solve systems of linear equations.
Gaussian Blur blurs image but you can use it to soften mask edges and to create different effects like Glamour glow.
It is used when there are a large number of independent, identically distributed variables.
The gaussian elimination is used to solve many linear equations with many unknown varaibles at once. [See related link below to find out how to do it]. This is used alot by engineers you know ceratin variables in there structures and want to find out what the stress and strain is in certain areas. They make up there linear equations and then they can use the gaussian elimination method to find the unknown variables.