Question

Consider a stochastic process Z(t)=X(t)Y(t) where X(t), Y(t) are independent and wide-sense stationary(WSS) . Is Z(t)...

Consider a stochastic process Z(t)=X(t)Y(t) where X(t), Y(t) are independent and
wide-sense stationary(WSS) . Is Z(t) wide-sense stationary? Why?

Homework Answers

Answer #1

Given

Z(t)=X(t)Y(t), where X(t), Y(t) are independent and
wide-sense stationary(WSS)

consider

E[Z(t)] = E[X(t)Y(t)]

= E[X(t)] E[Y(t)]

= Constant . Constant

= Constant

Hense Z(t) is a 1st order stationary random process. ------- (1)

Consider

RZZ (t,t+T) = E[Z(t) Z(t+T)]

  = E[X(t) Y(t) X(t+T) Y(t+T)]

  = E[X(t) X(t+T)] E[Y(t) Y(t+T)]

  = RXX(T).Ryy(T)

  = Rzz(T)

Hense Z(t) is a 2nd order stationary random process. ------ (2)

From equations (1) and (2) we can clearly say that if,Z(t)=X(t)Y(t) then Z(t) wide-sense stationary.

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Let X(t) and Y(t) be independent, wide-sense stationary random process with zero means and the same...
Let X(t) and Y(t) be independent, wide-sense stationary random process with zero means and the same covariance function Cx(t) Let Z(t) be defined by Z(t) = X(t)coswt + Y(t)sinwt Find the joint pdf of X(t1) and X(t2) in part b
Given the process x(t) = a + bt + e(t), where e(t) is a white noise...
Given the process x(t) = a + bt + e(t), where e(t) is a white noise process with known variance, show that y(t) = x(t) - x(t-1) is a stationary time series.
Consider the ARIMA(0,1,1) model (1−B)zt = (1−0.8B)at. (a) Is the stochastic process for zt stationary ?...
Consider the ARIMA(0,1,1) model (1−B)zt = (1−0.8B)at. (a) Is the stochastic process for zt stationary ? Explain. (b) Show that this model can be written as zt = ¯ zt−1 + at where ¯ zt−1 =P ∞ j=1 πjzt−j. Derive the coefficients πj and show thatP∞ j=1 πj = 1. (c) Write the one- and two-step-ahead forecasts in the form zt(1) = ∞ X j=1 πjzt−j+1 and zt(2) = ∞ X j=1 π(2) j zt−j+1 Express π(2) j in terms...
For the 3-CNF f = (x’ +y’+z)& (x+y’+z’)&(x+y+z’)& (x’+y+z)&(x’+y+z’) &(x+y+z) where “+” is or, “&” is...
For the 3-CNF f = (x’ +y’+z)& (x+y’+z’)&(x+y+z’)& (x’+y+z)&(x’+y+z’) &(x+y+z) where “+” is or, “&” is and operations, “ ’ ” is negation. a)give 0-1 assignment to variables such that f=1    x= ______ y= ______ z= ____ f=0    x= ______ y= ______ z= ____ - b) Draw the corresponding graph and mark the maximum independent set. (you can draw on paper, scan and insert here)
Let T: R^3----> R^3 where T(x,y,z) = (x-2z,y+z,x+2y) . Is T a one-to-one transformation? Is the...
Let T: R^3----> R^3 where T(x,y,z) = (x-2z,y+z,x+2y) . Is T a one-to-one transformation? Is the range of T R^3 ? Explain
Consider the mapping R^3 to R^3 T[x,y,z] = [x-2z, x+y-z, 2y] a) Show that T is...
Consider the mapping R^3 to R^3 T[x,y,z] = [x-2z, x+y-z, 2y] a) Show that T is a linear Transformation b) Find the Kernel of T Note: Step by step please. Much appreciated.
Let X and Y be independent exponentially distributed stochastic variables with parameters α and β. Find...
Let X and Y be independent exponentially distributed stochastic variables with parameters α and β. Find the distribution function (c.d.f.) of X / Y. Please show work involved and general equations used. As much supplementary text as possible will be greatly appreciated
1. Consider the relations R = {(x,y),(y,z),(z,x)} and S = {(y,x),(z,y),(x,z)} on {x, y, z}. a)...
1. Consider the relations R = {(x,y),(y,z),(z,x)} and S = {(y,x),(z,y),(x,z)} on {x, y, z}. a) Explain why R is not an equivalence relation. b) Explain why S is not an equivalence relation. c) Find S ◦ R. d) Show that S ◦ R is an equivalence relation. e) What are the equivalence classes of S ◦ R?
Consider two events. Give an example of coordinates x,y,z,t and x’,y’,z’,t’ and relative velocity of the...
Consider two events. Give an example of coordinates x,y,z,t and x’,y’,z’,t’ and relative velocity of the two frames u, such that event 1 occurs first in the unprimed reference frame, but event 2 occurs first in the primed reference frame. The example must use special relativity and show it works using numbers not just concept
consider the joint density function Fx,y,za (x,y,z)=(x+y)e^(-z) where 0<x<1, 0<y<1, z>0 find the marginal density of...
consider the joint density function Fx,y,za (x,y,z)=(x+y)e^(-z) where 0<x<1, 0<y<1, z>0 find the marginal density of z : fz (z). hint. figure out which common distribution Z follows and report the rate parameter integral (x+y)e^(-z) dz (x+y)(-e^(-z) + C is my answer 1. ???