(10 pts) A random process has sample function of the form x(t) random variable uniformly distributed...
The sample function X(t) of a stationary random process Y(t) is given by X(t) = Y(t)sin(wt+Θ) where w is a constant, Y(t) and Θ are statistically independent, and Θ is uniformly distributed between 0 and 2π. Find the autocorrelation function of X(t) in terms of RYY(τ).
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...
Let X(t) be a wide-sense stationary random process with the autocorrelation function : Rxx(τ)=e-a|τ| where a> 0 is a constant. Assume that X(t) amplitude modulates a carrier cos(2πf0t+θ), Y(t) = X(t) cos(2πf0t+θ) where θ is random variable on (-π,π) and is statistically independent of X(t). a. Determine the autocorrelation function Ryy(τ) of Y(t), and also give a sketch of it. b. Is y(t) wide-sense stationary as well?
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) -...
A random process has a sample function of the form: Where: Y and are constants (NOT random variables) and is a random variable that is uniformly distributed between 0 and . Find: the mean value, the mean square value and variance of Show that the random process is wide-sense-stationary (wss) and its auto correlation depends only on which is the difference in time between and foe a give waveform
7) (20 pts) Let X(t) = At be a random process, such that A is N(0, 1). , ??(t)-EX(t)]. (a) Find mean of the random process X(t) (b) Find the auto-correlation function of X, Rx(t1,t2) - E[X (ti)X (t2)
Let a random process x(t) be defined by x(t) = At + B (a) If B is a constant and A is uniformly distributed between-1 and +1, sketch a few sample functions (b) If A is a constant and B is uniformly distributed between 0 and 2, sketch a few sample functions c) Evaluate (r2(t)) d) Evaluate x2(t) e) Using the results of part c) and d), determine whether the process is ergodic for the averages Let a random process...
A(t) is a wide-sense stationary random process and is a random variable distributed uniformly over [0, 211]. Furthermore, is independent of A(t). Three random processes X(t), Y(t), and Z(t) are given by X(t) = A(t) cos(20ft + 0) Y(t) = A(t) cos(507t + 0) z(t) = X(t) + y(t) a. Show that X(t) and Y(t) are stationary in the wide sense. b. Show that Z(t) is not stationary in the wide sense.
(9) 112 pts] An exponentially distributed random variable, call it X, has the following probability density function: f(x)-Be-ex , x > 0, θ > 0. Note that E(X) and VX-สั่ For the rest of this question, assume that you have a data set xn1 consisting of a random sample of N observations of X (a) Derive two different Method of Moments estimators for θ. HINT: remember that the MOM is based on the analogy principle, or the idea that sample...
(9) 112 pts] An exponentially distributed random variable, call it X, has the following probability density function: f(x)-Be-ex , x > 0, θ > 0. Note that E(X) and VX-สั่ For the rest of this question, assume that you have a data set xn1 consisting of a random sample of N observations of X (a) Derive two different Method of Moments estimators for θ. HINT: remember that the MOM is based on the analogy principle, or the idea that sample...