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Posted By: vivekanandan       Member Level: Gold       Posted Date: 18 Jun 2008

2008 2008 Anna University Electronics and Communication B.E/B.Tech DEGREE EXAMINATION, APRIL/MAY 2008 Question paper Question paper



Course: B.E Electronics and Communication   University: Anna University




B.E/B.Tech DEGREE EXAMINATION, APRIL/MAY 2008

Fourth Semester

Electronics and communication Engineering

MA1254-RANDOM PROCESSES

(Regulation 2004)

Time:Three hours Maximum:100 marks

Answer ALL questions

PART A –(10*2=20marks)

1. State the axioms of probability.

2. Define central moments of a random variable.

3. Write the moment generating function of Geometric distribution.

4. Write a note on functions of a random variable.

5. If the function f(x,y)=c(1-x)(1-y),0<1,0<1,y<1>

function, find the value of c.

6. If Y=-2x+3, find the cov(X,Y).

7. What is a Markov process?

8. When is a stochastic process said to be ergodic?

9. What is meant by autocorrelation?

10. Write a note on a linear system.

PART – B(16X5=80 marks)

11. (a)(i) Members of a firm rent cars from three rental agencies. 60 percent

from agency 1, 30 percent from agency 2 and 10 percent from agency3.

If the percentages of the cars that tune-up are 9%,20% and 6%

respectively from agencies 1,2 and 3, what is the probability that it comes

from rental agency 2 if a rental car delivered to the firm needs tune-up?

(ii) Find the probability distribution of the total number of heads obtained in

four tosses of a balanced coin. Hence obtain the MGF of X, mean of X

and variance of X.

Or

(b)(i) In a small library there are 1000 books, among which 500 are scientific.

Among the scientific books are100 which belong to Engineering. Three

books are chosen at random, the chosen books being replaced each time.

What is the probability of getting (1)all three scientific books,(2) three

scientific books among which only one is an engineering book and (3) at

least one of three is an engineering book.

(ii) If X has the distribution function

0 x<1

1/3 1= x <4

½ 4 = x <>

5/6 6= x <>

1 x= 10

Find

(1) The probability distribution of X.

(2) P ( 2<>

(3) Mean of X.

(4) Variance of X.

12. (a)(i) Obtain the MGF of Poisson distribution and hence compute the

first four moments.

(ii) State and explain the properties of Normal N( µ , s ² ) distribution.

Or

(b)(i) Find the variance of a random variable X which follows Negative

Binomial distribution.

(ii) State the density function of Weibull distribution and mention its

properties.

(iii) What is the variance of the random variable X which is Uniformly

distributed?

13. (a)(i) Given the joint probability density function of (X,Y):

f(x,y) = { e^-(x+y) x>0,y>0

0, elsewhere

Find the marginal densities of X and Y. Are X and Y independent?

(ii) Find the correlation between X and Y if the joint probability density

of X and Y is f(x,y) = { 2 for x>0, y>0 ,x+y<1

0 elsewhere

Or

(b)(i) Given the joint probability density

f (x,y) = { 2/3 (x +2y ) for 0<>

0 elsewhere

Find the marginal densities, conditional density of X given Y=y

and P ( X = ½ / y=1/2).

(ii) Let the joint probability distribution of X and Y be given by

x

-1 0 1

-1 1/6 1/3 1/6

y 0 0 0 0

1 1/6 0 1/6

Show that their covariance is zero even though the two random

variables are not independent.

14. (a)(i) Define a stationary stochastic process. If {X(t) ,t e T} is a process

with probability distribution.

P(X(t) = n) = { (at)^ n-1/ (1+ at)^n+1 , n=1,2…….

at/ 1+at n=0

Verify whether {X(t)} is a stationary process.

(ii) Write a detailed note on Normal process.

Or

(b)(i) Distinguish between ‘stationary’ and weakly stationary stochastic

processes. Give an example to each type. Show that Poisson

process is an evolutionary process.

(ii) Write a critical note on ‘sine wave’ process and its applications.

15.(a)(i) For a linear system with random input x(t), the impulse response h(t)

and output y(t), obtain the cross correlation function Ryx(T) and the

output autocorrelation function Ryy(T).

(ii) Starting your assumptions, discuss the relationship between cross

power spectrum and cross spectrum.

Or

(b)(i) Given a stationary random process X(t) = 10 cos (100t+?) where ? ? (-p, p)

followed Uniform distribution. Find the autocorrelation function of the

process.

(ii) Auto correlation function of an ergodic process {X(t) =X} is

Rxx(T)= { 1- |T| , |T|=1

0, otherwise . Obtain the spectral density of X.





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