In my study material I came across this:
Interpretation of the autocorrelation function of a WSS process:
The autocorrelation function RX ( τ ) measures the correlation between two random variables X ( t ) and X ( t + τ ). If RX ( τ ) drops quickly with respect to τ , then the X ( t ) and X ( t + τ ) will be less correlated for large τ . This in turn means that the signal has lot of changes with respect to time. Such a signal has high frequency components. If RX ( τ ) drops slowly, the signal samples are highly correlated and such a signal has less high frequency components.
According to me this is possible only if the mean of Random Process is considered to be 0, because if the covariance is 0 and the mean is 5 then RX ( τ ) would be 25 which would give a false impression that the process is highly correlated as it does not quickly drop but its uncorrelated. Am I right with this justification?