The random process X(t) is defined by X(t) = X cos 27 fot + Y sin...
324. Consider the random process X(t) = A + Bt2 for - <t < oo, where A and B are two statistically independent Gaussian random variables, each with zero mean and variance o?. a) Plot two sample functions of X(t). b) Find E{X(0)} c) Find the autocorrelation function Rx(t,t +T). d) Find the pdf of the random variable Y = X(1). e) Is X(t) a Gaussian process? Prove your result.
3.34. Let (X.(t) and (x.(e)) denote two statistically independent zero mean stationary Gaussian random processes with common power spec- tral density given by Ste (f) = S, (f) = 112B(f) Watt/Ha Define X (t) X( t) cos(2 fo t) - Xs (t) sin(2r fot) ) - Xs(t) sin(2T fot where fo》 B (c) Find the pdf of X(0). (d) The process X(t) is passed through an ideal bandpass filter with transfer function given by otherwise. Let Y(t) denote the output...
2. Consider the random process x(t) defined by x(t) a cos(wt + 6).where w and a are constants, and 0 is a random variable uniformly distributed in the range (-T, ) Sketch the ensemble (sample functions) representing x(t). (2.5 points). a. b. Find the mean and variance of the random variable 0. (2.5 points). Find the mean of x(t), m (t) E(x(t)). (2.5 points). c. d. Find the autocorrelation of x(t), R (t,, t) = E(x, (t)x2 (t)). (5 points)....
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...
ANSWER SHOULD BE NEAT AND CLEAN Consider the random process W (r) = X cos(27/01) + Y cos(2π.fot) where A andY are uncorrrelated random variables, each with expected value 0 and variance σ2. Find the autocorrelation RW(t, τ). Is W(t) wide sense Consider the random process W (r) = X cos(27/01) + Y cos(2π.fot) where A andY are uncorrrelated random variables, each with expected value 0 and variance σ2. Find the autocorrelation RW(t, τ). Is W(t) wide sense
P9.3 A random process X(t) has the following member functions: x1 (t) -2 cos(t), x2(t)2 sin(t), x3(t)- 2 (cos(t) +sin(t)),x4t)cost) - sin(t), xst)sin(t) - cos(t).Each member function occurs with equal probability. (a) Find the mean function, Hx (t). (b) Find the autocorrelation function, Rx(t1,t2) (c) Is this process WSS? Is it stationary in the strict sense?
2. Consider the random process x(t) defined by x(t) a cos(wt 6), where w and 0 are constants, and a is a random variable uniformly distributed in the range (-A, A). a. Sketch the ensemble (sample functions) representing x(t). (2.5 points). b. Find the mean and variance of the random variable a. (5 points). c. Find the mean of x(t), m(t) E((t)). (5 points). d. Find the autocorrelation of x(t), Ra (t1, t2) E(x (t)x2 )). (5 points). Is the...
3.34. Let fXc(t)) and (X,(t)J denote two statistically independent zero n stationary Gaussian random processes with common power spec- tral density given by SX (f) = SX (f) = 112B(f) watt/Hz. Define x(t) = Xe(t) cos(2tht)--Xs(t) sin(2tht) where fo 》 (a) Is X(t) a Gaussian process? (b) Find the mean E(X (t), autocorrelation function Rx (t,t + T), and power spectral density Sx(f) of the process X(t) (c) Find the pdf of X(O) (d) The process X(t) is passed through...
5. Let X(t) be a random process which consist of the summation of two sinusoidal components as t(t) = A cos(wt) + B sin(wt), where A and B are independent zero mean random variables. (a) (5 points) Find the mean function, pat). (b) (5 points) Find the autocorrelation function Ratta). (e) (5 points) Under what conditions is i(t) wide sense stationary (WSS)?! The questions form the textbook : 1.4, 2.1, 2.4, 2.6 Some trigonometric formulas: cos(A + B) = cos...
Consider a random process X(t) defined by X(t) - Ycoset, 0st where o is a constant 1. and Y is a uniform random variable over (0,1) (a) Classify X(t) (b) Sketch a few (at least three) typical sample function of X(t) (c) Determine the pdfs of X(t) at t 0, /4o, /2, o. (d) EX() (e) Find the autocorrelation function Rx(t,s) of X(t) (f) Find the autocovariance function Rx(t,s) of X(t) Consider a random process X(t) defined by X(t) -...