# Parameters of a white Gaussian noise process

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.

https://brainmass.com/engineering/power-engineering/parameters-white-gaussian-noise-process-11643

#### Solution Preview

1.)

because,

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 Summary

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