Purchase Solution

Parameters of a white Gaussian noise process

Not what you're looking for?

Ask Custom Question

A white Gaussian noise process X(t) with power spectral density (PSD) N0/2=0.1 is input to an LTI filter with a transfer function H(f) given by

H(f) = 2, |f| <= W and 0, otherwise

The output is denoted Y(t).

(1) Find the autocorrelation function RX(t) of X(t).
(2) Find E[Y(t)].
(3) Find the PSD of Y(t).
(4) Determine a W such that E[Y2(t)] = 10.
(5) Find the first-order PDF of Y(t), i.e., fY(t)(y), when E[Y2(t)] = 10.
(6) Find the probability P(Y(t)>3), when E[Y2(t)] = 10.

Purchase this Solution

Solution Summary

The parameters of a white Gaussian noise process are found. The autocorrelation functions are given. The solution is 260 words, equations and explanations.

Solution Preview

Sx(f) = integral(-infinity to +infinity) [Rx(t)*exp(-i.2.pi.f.t)*dt]
=>Rx(t) = (1/(2.pi))*integral(-inf to +inf)[Sx(f)*exp(i.2.pi.f.t)*df]
Sx(f) = 0.1
=>Rx(t) = (0.1/(2.pi))*integral(-inf to +inf)[exp(i.2.pi.f.t)*df]
=> Rx(t) =(0.1/(2.pi))*2*integral(0 to +inf)[cos(2.pi.f.t)*df]
=> Rx(t) =(0.1/(2.pi))*2*pi*delta(t) = 0.1*delta(t)
where, delta(t) is the sampling function. --Answer

2.) because,
Y(f) = ...

Solution provided by:
  • BEng, Allahabad University, India
  • MSc , Pune University, India
  • PhD (IP), Pune University, India
Recent Feedback
  • " In question 2, you incorrectly add in the $3.00 dividend that was just paid to determine the value of the stock price using the dividend discount model. In question 4 response, it should have also been recognized that dividend discount models are not useful if any of the parameters used in the model are inaccurate. "
  • "feedback: fail to recognize the operating cash flow will not begin until the end of year 3."
  • "Answer was correct"
  • "Great thanks"
  • "Perfect solution..thank you"
Purchase this Solution

Free BrainMass Quizzes
Architectural History

This quiz is intended to test the basics of History of Architecture- foundation for all architectural courses.