Which effects on the covariance matrix provides the information that a random variable has a zero mean noise distribution? Thanks in advance for your answers.
2026-03-25 01:16:45.1774401405
Effects of zero mean on covariance matrix
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Covariance is invariant under translations: $Cov(X-a,Y-b)=E[X-a-E[X-a],Y-b-E[Y-b]]=E[X-E[X],Y-E[Y]]=Cov(X,Y)$ for constants $a,b$.
Therefore, it is irrelevant what the mean is, as long as it exists.