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Probability, Random Variables, and Random Processes: Theory and Signal Processing Applications
book

Probability, Random Variables, and Random Processes: Theory and Signal Processing Applications

by John J. Shynk
November 2012
Intermediate to advanced
794 pages
22h 9m
English
Wiley-Interscience
Content preview from Probability, Random Variables, and Random Processes: Theory and Signal Processing Applications

5.12 CONDITIONAL EXPECTATION

The conditional probability of events A and B in the abstract probability space was introduced in Chapter 2. There we discussed how conditioning on event B reduces the sample space for event A such that we can write

(5.112) Numbered Display Equation

assuming . In Chapter 3, we considered conditional pdfs which have a form analogous to (5.112):

(5.113) Numbered Display Equation

and likewise for conditional pmfs. The conditional expectation, which is also called the conditional mean, follows from these expressions.

Definition: Conditional Expectation The conditional expectation of random variable X given that random variable Y takes on the value y is

(5.114) Numbered Display Equation

Observe that is a nonrandom function of y, such that we can write . The conditional expectation given random variable Y is itself a random variable because ...

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Publisher Resources

ISBN: 9781118393956Purchase book