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Question 2 12 Marks) a) Prove that for a Gaussian (normal) random variable, X, with mean...
8. A Gaussian random variable x with a mean and variance of ax and Ox? respectively...
8. A Gaussian random variable x with a mean and variance of ax and Ox? respectively goes through a linear transformation of y=ax +b, where a and b are any real constants. Determine the probability density function of y, also give its mean and variance. (5 points).
1. The random variable X is Gaussian with mean 3 and variance 4; that is X...
1. The random variable X is Gaussian with mean 3 and variance 4; that is X ~ N(3,4). $x() = veze sve [5] (a) Find P(-1 < X < 5), the probability that X is between -1 and 5 (inclusive). Write your answer in terms of the 0 () function. [5] (b) Find P(X2 – 3 < 6). Write your answer in terms of the 0 () function. [5] (c) We know from class that the random variable Y =...
3. (10 pts.) X is a Gaussian random variable with E{X} = 2 and Var(X) =...
3. (10 pts.) X is a Gaussian random variable with E{X} = 2 and Var(X) = 16. Let Y = 3X +1. Determine the probability: Pr(Y > 2)
5. [20 points] X is a Gaussian random variable with zero mean and variance σ2. This...
5. [20 points] X is a Gaussian random variable with zero mean and variance σ2. This random variable is passed through a hard-limiter device whose input-output relation is b r <0 Find the PDF of the output random variable Yg(X)
A Gaussian random variable X has mean 2 and variance 4 a) Find P(X < 3)....
A Gaussian random variable X has mean 2 and variance 4 a) Find P(X < 3). (b) Find P(1 < X < 3) (c) Find P({X > 4}|{X > 3}) (d) Let Y = X^2 . Find E[Y].
5. A random variable X ∼ N (µ, σ2 ) is Gaussian distributed with mean µ...
5. A random variable X ∼ N (µ, σ2 ) is Gaussian distributed with mean µ and variance σ 2 . Given that for any a, b ∈ R, we have that Y = aX + b is also Gaussian, find a, b such that Y ∼ N (0, 1) Please show your work. Thanks!
Suppose X is a Gaussian random variable with mean 2 and variance 4. Find E(eX/2).
Suppose X is a Gaussian random variable with mean 2 and variance 4. Find E(eX/2).
X is a Gaussian random variable with zero mean and variance ơ2 This random variable 5...
X is a Gaussian random variable with zero mean and variance ơ2 This random variable 5 20 points is passed through a quantizer device whose input-output relation is g(z) = Zn, for an x < an+1, 1 N where In lies in the interval [an, Qn+1) and the sequence fa, a2, al z-00, aN41 # oo, and for i > j we have ai > aj. Find the PMF of the output random variable Y g(X). aN+1) satisfies the conditions
(12 points) The random variables X1, X2, and X; are jointly Gaussian with the following mean...
(12 points) The random variables X1, X2, and X; are jointly Gaussian with the following mean vector and covariance matrix: 54 2 07 2 5 -1 0-1 The random variable Y is formed from X1, X2, and X; as follows: Y=X1 - X2 + X3 +4. Determine P( Y> 3).
1. Let X~b(x; n, p) (a) For n 6, p .2, find () Prx> 3), (ii) Pr(x23), (ii) Pr(x (b) For n = 15, p= .8, find (i) Pr(X-2), (ii) Pr(X-12), (iii) Pr(X-8). (c) For n 10, find p so that Pr(X 2 8)6778....
1. Let X~b(x; n, p) (a) For n 6, p .2, find () Prx> 3), (ii) Pr(x23), (ii) Pr(x (b) For n = 15, p= .8, find (i) Pr(X-2), (ii) Pr(X-12), (iii) Pr(X-8). (c) For n 10, find p so that Pr(X 2 8)6778. く2). 2. Let X be a binomial random variable with μ-6 and σ2-2.4. Fin (a) Pr(X> 2) (b) Pr(2 < X < 8). (c) Pr(Xs 8).
1. Let X~b(x; n, p) (a) For n 6, p...
8. A Gaussian random variable x with a mean and variance of ax and Ox? respectively goes through a linear transformation of y=ax +b, where a and b are any real constants. Determine the probability density function of y, also give its mean and variance. (5 points).
1. The random variable X is Gaussian with mean 3 and variance 4; that is X ~ N(3,4). $x() = veze sve [5] (a) Find P(-1 < X < 5), the probability that X is between -1 and 5 (inclusive). Write your answer in terms of the 0 () function. [5] (b) Find P(X2 – 3 < 6). Write your answer in terms of the 0 () function. [5] (c) We know from class that the random variable Y =...
3. (10 pts.) X is a Gaussian random variable with E{X} = 2 and Var(X) = 16. Let Y = 3X +1. Determine the probability: Pr(Y > 2)
5. [20 points] X is a Gaussian random variable with zero mean and variance σ2. This random variable is passed through a hard-limiter device whose input-output relation is b r <0 Find the PDF of the output random variable Yg(X)
X is a Gaussian random variable with zero mean and variance ơ2 This random variable 5 20 points is passed through a quantizer device whose input-output relation is g(z) = Zn, for an x < an+1, 1 N where In lies in the interval [an, Qn+1) and the sequence fa, a2, al z-00, aN41 # oo, and for i > j we have ai > aj. Find the PMF of the output random variable Y g(X). aN+1) satisfies the conditions
(12 points) The random variables X1, X2, and X; are jointly Gaussian with the following mean vector and covariance matrix: 54 2 07 2 5 -1 0-1 The random variable Y is formed from X1, X2, and X; as follows: Y=X1 - X2 + X3 +4. Determine P( Y> 3).
1. Let X~b(x; n, p) (a) For n 6, p .2, find () Prx> 3), (ii) Pr(x23), (ii) Pr(x (b) For n = 15, p= .8, find (i) Pr(X-2), (ii) Pr(X-12), (iii) Pr(X-8). (c) For n 10, find p so that Pr(X 2 8)6778. く2). 2. Let X be a binomial random variable with μ-6 and σ2-2.4. Fin (a) Pr(X> 2) (b) Pr(2 < X < 8). (c) Pr(Xs 8).
1. Let X~b(x; n, p) (a) For n 6, p...
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