{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Review of Random Processes1

# Review of Random Processes1 - Random Processes A Random...

This preview shows pages 1–2. Sign up to view the full content.

3/5/2010 1 Review of Random Processes Random Processes A Random Variable that is a function of time is called a Random Process. A Random Process X(t, ζ ) is a collection (ensemble) of all possible sample functions (waveforms) of the random variable X(t). A Random Process is a collection of an infinite number of Random Variables. Figure 9.1 Random process for representing the temperature of a city. Moments   2 1 2 1 2 1 2 1 2 1 2 1 2 1 ) , ; , ( ) ( ) ( ) , ( : ation autocorrel ) ; ( )] ( [ ) ( : mean 2 1 x dx t t x x p x x X X t X t X t t R dx t x xp t X E t X x x X X Figure 9.4 Autocorrelation functions for a slowly varying and a rapidly varying random process. The autocorrelation is a measure of the similarity of the amplitudes at t1 and t2. The rapidity of the amplitude change, and hence the autocorrelation, contains frequency information of the process. Strict-Sense Stationary (SSS) and Wide-Sense Stationary (WSS) A random process is strict-sense stationary (SSS) if all

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 3

Review of Random Processes1 - Random Processes A Random...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online