Multiplying every element in Covariance matrix This is regarding article in this link which explains Kalman filter. In this article at one point in equation 4 author says
If we multiply every point in a distribution by a matrix A, then what happens to its covariance matrix Σ?
Well, it’s easy. I’ll just give you the identity:

How can derive this equation?

We have
$$
Cov(Ax) = \Bbb E((Ax)(Ax)^T) = \Bbb E(A(xx^T)A^T) = A\Bbb E(xx^T) A^T = A Cov(x)A^T
$$
