MA8402 Important Questions Probability And Queuing Theory
MA8402 Important Questions Probability And Queuing Theory Regulation 2017 Anna University free download. Probability And Queuing Theory Important Questions MA8402 pdf free download.
Sample MA8402 Important Questions Probability And Queuing Theory:
1. Define Random process. (Pg – 337)
Solution: A random process is a collection of random variables
{X(s,t)} that are functions of a real variable, namely t where s∈ (sample space) and t∈T(parameter set). MA8402 Important Questions Probability And Queuing Theory
2. Give the classification of Random Processes.(Pg – 338)
Solution: Discrete random sequence, Continuous random sequence,
Discrete random process, Continuous random process.
3. Define Stationary processes. (Pg – 339)
Solution: If certain probability distribution or averages do not depend
on t, then the random process {X(t)} is called stationary. MA8402 Important Questions Probability And Queuing Theory
4. Define SSS process.(Pg – 340)
Solution: A random process is called a strongly stationary process or
strict sense stationary process, if all its finite dimensional distributions
are invariant under translation of time parameter.
5. Define WSS process.(Pg – 341)
Solution: A random process {X(t)} with finite first and second order
moments is called a weakly stationary process or covariance
stationary process or wide-sense stationary process, if its mean is a
constant and the auto correlation depends only on the time difference.
6. Is Poisson process covariance stationary? Justify.(Pg – 343)
Solution: No. Mean of poisson process = λt ≠ a constant. MA8402 Important Questions Probability And Queuing Theory
7. Show that the random process X(t)=A cos(w0t + θ) is WSS,
if A and w0 are constants and θ is a uniformly distributed RV in (0 , 2π).
(Pg – 344)
Solution: Mean = 0 = a constant.
Autocorrelation = (A2/2)cosw0 (t1 – t2).
Hence WSS process.
8. If {X(t)} is a wss process with autocorrelation R(τ)=Ae-α|τ| ,
determine the second-order moment of the RV X(8) – X(5).
Solution: 2A(1 – e-3α) MA8402 Important Questions Probability And Queuing Theory
9. Define Markov process. (Pg – 446)
Solution: Markov process is one in which the future value is
independent of the past values, given the present value
| Subject name | Probability And Queuing Theory |
| Short Name | PQT |
| Semester | 4 |
| Subject Code | MA8402 |
| Regulation | 2017 regulation |
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