Probability density function after filtering Hello, I am trying to find how a random variable will transform once gone through a filter. For example, I have a random sequence x(t), going through a filter h(t). Thus, y(t) = x(t)*h(t) ; % '*' is convolution. Now I want to find out how the PDF of y(t). Is there a certain analytical method to find this? Suppose x(t) is Gaussian with a certain mean and variance. How will this mean and variance will be chaned when this signal goes through a low-pass filter. (Going through a low pass filter will give a Gaussian signal due to Central Limit theorem, but how will the PDF characteristics change). Any advice or references are greatly appreciated. Thank you.