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Unformatted text preview: ECE 5510: Random Processes Lecture Notes Fall 2009 Lecture 8 Today: (1) Expectation for cts. r.v.s (Y&G 3.3), (2) Condi- tional Distributions (Y&G 2.9, 3.8) • Exam is Tuesday Sept 29. • Today’s lecture is the last material covered in the exam. Tues- day’s is not. • HW 3 due today at 5pm. • Thu Sept 25 is a review session. Bring questions . • HW 4 due Thu Sept 25 at 10:45 am at start of lecture . All out of Yates & Goodman: 2.8.6, 2.8.8, 2.9.5, 3.7.2, 3.7.3, 3.8.5. Short list: Lectures 1-8, Chapter 1,2,3 What don’t we have to worry about for the exam? • 1.10, 1.11 (reliability, Matlab) • 2.10 (Matlab) • 3.6 (mixed r.v.s), 3.9 (Matlab) 1 Expectation for Continuous r.v.s Expression X is a discrete r.v. X is a continuous r.v. E X [ X ] = ∑ x ∈ S X xP X ( x ) = integraltext S X xf X ( x ) E X [ g ( X )] = ∑ x ∈ S X g ( x ) P X ( x ) = integraltext S X g ( x ) f X ( x ) E X [ aX + b ] = aE X [ X ] + b = aE X [ X ] + b E X [ X 2 ] 2 nd moment = ∑ x ∈ S X x 2 P X ( x ) = integraltext S X x 2 f X ( x ) Var X [ X ] = E X [( X- μ X ) 2 ], μ X = E X [ X ] = ∑ x ∈ S X ( x- μ X ) 2 P X ( x ) = integraltext S X ( x- μ X ) 2 f X ( x ) Example: Variance of Uniform r.v. Let X be a continous uniform r.v. on ( a,b ), with a,b > 0. 1. What is E X [ X ]? It is integraldisplay b a x b- a dx = 1 2( b- a ) x 2 vextendsingle vextendsingle b a = b 2- a 2 2( b- a ) = b + a 2 . ECE 5510 Fall 2009...
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This note was uploaded on 09/15/2011 for the course ECE 5510 taught by Professor Chen,r during the Fall '08 term at Utah.
- Fall '08