Presentation is loading. Please wait.

Presentation is loading. Please wait.

Sep 20, 2005CS477: Analog and Digital Communications1 Random variables, Random processes Analog and Digital Communications Autumn 2005-2006.

Similar presentations


Presentation on theme: "Sep 20, 2005CS477: Analog and Digital Communications1 Random variables, Random processes Analog and Digital Communications Autumn 2005-2006."— Presentation transcript:

1 Sep 20, 2005CS477: Analog and Digital Communications1 Random variables, Random processes Analog and Digital Communications Autumn 2005-2006

2 Sep 20, 2005CS477: Analog and Digital Communications2 Random Variables Outcomes and sample space Random Variables Mapping outcomes to: Discrete numbers  Discrete RVs Real line  Continuous RVs Cumulative distribution function One variable Joint cdf

3 Sep 20, 2005CS477: Analog and Digital Communications3 Random Variables Probability mass function (discrete RV) Probability density function (cont. RV) Joint pdf of independent RVs Mean Variance Characteristic function (IFT of pdf)

4 Sep 20, 2005CS477: Analog and Digital Communications4 Random Processes Mapping of an outcome (of an experiment) to a range set R where R is a set of continuous functions Denoted as or simply For a particular outcome is a deterministic function For or simply is a random variable

5 Sep 20, 2005CS477: Analog and Digital Communications5 Random Processes Mean Autocorrelation Autocovariance

6 Sep 20, 2005CS477: Analog and Digital Communications6 Random Processes Cross-correlation (Processes are orthogonal if ) Cross-covariance

7 Sep 20, 2005CS477: Analog and Digital Communications7 Example

8 Sep 20, 2005CS477: Analog and Digital Communications8 Example Mean is constant and autocorrelation is dependent on

9 Sep 20, 2005CS477: Analog and Digital Communications9 Example

10 Sep 20, 2005CS477: Analog and Digital Communications10 Stationary and WSS RP Stationary Random Process (RP) Wide sense stationary (WSS) RP Mean constant in time Autocorrelation depends only on Stationary  WSS (Converse not true!)

11 Sep 20, 2005CS477: Analog and Digital Communications11 Power Spectral Density (PSD) Defined for WSS processes Provides power distribution as a function of frequency Wiener-Khinchine theorem PSD is Fourier transform of ACF


Download ppt "Sep 20, 2005CS477: Analog and Digital Communications1 Random variables, Random processes Analog and Digital Communications Autumn 2005-2006."

Similar presentations


Ads by Google