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Material Type: Notes; Class: Random Processes; Subject: Electrical and Computer Engr; University: University of Illinois - Urbana-Champaign; Term: Spring 2005;
Typology: Study notes
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University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering ECE 434: Random Processes Spring 2005 Solutions to Probability Review
Problem 1.
(a) True. If X, Y are conditionally independent on Z, then fXY |Z (x, y|z) = fX|Z (x|z) · fY |Z (y|z). Here fXY |Z (x, y|z) = (^) fZ^4 (z) e−zx^ · e−zy, X and Y components are uncoupled, thus they are conditionally independent. (b) True.
V ar(X + Y ) = E[(x + y − mx − my)^2 ] = E[((x − mx) + (y − my))^2 ] = E[(x − mx)^2 ] + E[(y − my)^2 ] = V ar(X) + V ar(Y ).
(c) False. P (A∪B) = P (A)+P (B)−P (A∩B) = P (A)+P (B)−P (A)P (B) 6 = P (A)+P (B).
(d) True. P (A ∪ B) = P (A) + P (B) − P (A)P (B) = P (A) + P (A) − P 2 (A) = 32 P (A). P (A) = 12.
(e) False. P (Y = 0) = P [X ≤ 0] = 12 , so this is not a continuous random variable.
Problem 1.
(a)
P (Y = 1) = P (Y = 1, X = 0) + P (Y = 1, X = 1) = P (Y = 1|X = 0)P (X = 0) + P (Y = 1|X = 1)P (X = 1) = p 2 · 1 2
(b) P (X = 0|Y = 1) = P^ (X^ = 0, Y^ = 1) P (Y = 1)
p 2 · (^12) 1+p 2 −p 1 2
= p^2 1 − p 1 + p 2
(c) We are asked to find the Bayes rule. Math aside, we can reason this out. The probability of making a mistake during the transmission, p 1 and p 2 , are both less than 1/2. That means more than half of the time, what we receive at Y is what was sent at source X.
When Y = 1:
Xˆ = arg max i=0, 1
P (X = i|Y = 1) = arg max i=0, 1
= arg max i=0, 1 {
p 2 1 − p 1 + p 2 ,^
1 − p 1 1 − p 1 + P 2 }
Since p 2 < 12 , 1 − p 1 > 12 , so Xˆ = 1. Similarly we can compute Xˆ when Y = 0. The Bayes decision rule is:
Xˆ =
1 when Y = 1 0 when Y = 0
P (E) = P (X = 0, Y = 1) + P (X = 1, Y = 0) = p^1 + 2 p^2.
Problem 1.
(a) We need fX (x) to integrate to 1:
1 =
b
αe−xdx = α · e−b
α = eb
(b)
E[X] = eb
b
xe−xdx = b + 1
(c) 1. E[X + Y ] = E[X] + E[Y ] = b + 1 + μ.
Problem 1.
(a) fX,Y (x, y) is constant over the shaded region, thus fX,Y (x, y) = 2, for 0 ≤ x ≤ y ≤ 1.
fX (x) =
fX,Y (x, y)dy =
x
2 dy = 2(1 − x), x ∈ [0, 1]
fY (y) =
fX,Y (x, y)dx =
∫ (^) y
0
2 dx = 2y, y ∈ [0, 1]
(b) No. fX,Y (x, y) 6 = fX (x) · fY (y).
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