Random Processes – 04 – Mean and Autocorrelation Function Example

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The previous videos provided definitions of the mean and autocorrelation function of a random process.

In this video we work with the random process X(t) = Asin(wc*t + theta) where both A and theta are random variables. We compute the mean function and autocorrelation function of this random process.

We show that the mean function is zero, and the autocorrelation function is just a function of the time difference t1-t2. Thus, this random process is a wide-sense stationary (WSS) random process (which we’ll formally define late).

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Stochastic Crossover Signal, Random Processes – 04 – Mean and Autocorrelation Function Example.

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The third important you should master on your method to success is cash management. Nevertheless, you must utilize another indicator so you can validate your conclusions. You can set your target simply above the mid band and take earnings.

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