Chapter 6 - Random Processes

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EE385 Class Notes 11/11/2014 John Stensby Updates at 6-1 Chapter 6 - Random Processes Recall that a Random variable X is a mapping between the sample space S and the extended real line R+. That is, X : S R+. A Random process ( stochastic process) is a mapping from the sample space into an ensemble of time functions (known as sample functions). To every S, there corresponds a function of time (a sample function) X(t; ). This is illustrated by Figure 6-1. Often, from the notation, we drop the variable, and write just X(t).

In general, a complete statistical description of a random process requires knowledge of all order distribution functions. Stationary Random Process A process X(t) is said to be stationary if its statistical properties do not change with time. More precisely, process X(t) is stationary if

  Statistical, Properties, Random, Statistical properties