Auto-covariance of a Wiener process of a function

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SUMMARY

The discussion focuses on determining the auto-covariance function for the process {X(t); t >= 0}, defined as X(t) = e^(-ct) * W(e^(2ct)), where W(t) is a Wiener process and c > 0 is a constant. The auto-covariance function is derived as C_X(t,τ) = α*e^(-c(2t+τ))*min{e^(2ct),e^(2c(t+τ))}. It is concluded that the process {X(t); t >= 0} is not stationary in the weak sense, as the auto-correlation function varies with time t.

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Homework Statement



Let {W(t); t >= 0} be a Wiener process. Determine the auto-covariance function for the process {X(t); t >= 0} defined by X(t) = e^(-ct) * W(e^(2ct)) for all t >= 0, where c > 0 is a constant.

Is {X(t); t >= 0} stationary in the wide sense?

Homework Equations



Is this possibly in the right direction?

The Attempt at a Solution



C_X (t,τ) = Cov(X(t), X(t+τ)) = Cov(e^(-ct) * W(e^(2ct)),e^(-c(t+τ)) * W(e^(2c(t+τ)))) = e^(-c(2t+τ))*Cov(W(e^(2ct)), W(e^(2c(t+τ)))) = α*e^(-c(2t+τ))*min{e^(2ct),e^(2c(t+τ))}.

The process is not stationary in the weak sense since the auto-correlation function (equal to the auto-covariance here?) varies with t.
 
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