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The input to a system is a Gaussian random variable below X with zero mean and variance of σ- as ...
Blem 4 , The input to a system is a Gaussian random variable below X with zero mean and variance ...
blem 4 , The input to a system is a Gaussian random variable below X with zero mean and variance of σ as shown System The output of the system is a random variable Y given as follows: bX (a) Determine the probability density function of the output Y b) Now assume that the following random variable is an input to the system at time t: where the amplitude A is a constant and phase θ is uniformly distributed over...
A stochastic process X() is defined by where A is a Gaussian-distributed random variable of zero ...
A stochastic process X() is defined by where A is a Gaussian-distributed random variable of zero mean and variance σ·The process Xt) is applied to an ideal integrator, producing the output YO)X(r) dr a. Determine the probability density function of the output Y) at a particular time t b. Determine whether or not Y) is strictly stationary Continuing with Problem 4.3, detemine whether or not the integrator output YC) produced in response to the input process Xit) is ergodic.
A...
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
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)
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 =...
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).
Suppose that X is a Gaussian Random Variable with zero mean and unit variance. Let Y=aX3...
Suppose that X is a Gaussian Random Variable with zero mean and unit variance. Let Y=aX3 + b, a > 0 Determine and plot the PDF of Y
2. The output Y of a binary communication system is a unit-variance Gaussian (Normal) random variable...
2. The output Y of a binary communication system is a unit-variance Gaussian (Normal) random variable with mean 0 when the input X is 0, and mean 1 when the input is 1. Assume that the input is 1 with probability p. (a) Determine fr(w). : If ( c) The receiver uses the following decision rule decide that input was 1; otherwise, decide that input was 0. Show that this decision rule leads to the following threshold rule: If Y...
5. A stationary random process X[n] is input to a discrete time LTI system with frequency...
5. A stationary random process X[n] is input to a discrete time LTI system with frequency response j“)-10 zero mean given as A(e nmay be expressed as where Wnlis a zero mea a-HS1 unit variancei.i.d. (independent identically distributed) Gaussian sequence and c, d are constants. Let Yl be the output random a)Determine the mean function for the output random sequence Yn in terms ofa, c and d b) Determine S7 (e), the power spectral density ofthe output random sequence Yn]...
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!
blem 4 , The input to a system is a Gaussian random variable below X with zero mean and variance of σ as shown System The output of the system is a random variable Y given as follows: bX (a) Determine the probability density function of the output Y b) Now assume that the following random variable is an input to the system at time t: where the amplitude A is a constant and phase θ is uniformly distributed over...
A stochastic process X() is defined by where A is a Gaussian-distributed random variable of zero mean and variance σ·The process Xt) is applied to an ideal integrator, producing the output YO)X(r) dr a. Determine the probability density function of the output Y) at a particular time t b. Determine whether or not Y) is strictly stationary Continuing with Problem 4.3, detemine whether or not the integrator output YC) produced in response to the input process Xit) is ergodic.
A...
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
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)
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 =...
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).
2. The output Y of a binary communication system is a unit-variance Gaussian (Normal) random variable with mean 0 when the input X is 0, and mean 1 when the input is 1. Assume that the input is 1 with probability p. (a) Determine fr(w). : If ( c) The receiver uses the following decision rule decide that input was 1; otherwise, decide that input was 0. Show that this decision rule leads to the following threshold rule: If Y...
5. A stationary random process X[n] is input to a discrete time LTI system with frequency response j“)-10 zero mean given as A(e nmay be expressed as where Wnlis a zero mea a-HS1 unit variancei.i.d. (independent identically distributed) Gaussian sequence and c, d are constants. Let Yl be the output random a)Determine the mean function for the output random sequence Yn in terms ofa, c and d b) Determine S7 (e), the power spectral density ofthe output random sequence Yn]...
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