With effect from the academic year 2015-2016
BIT 251
PROBABILITY AND RANDOM PROCESSES
Instruction |
4 |
Periods per week |
Duration of University Examination |
3 |
Hours |
University Examination |
75 Marks |
|
Sessional |
25 Marks |
Course Objectives:
- 1.To induce the ability to describe a random experiment in terms of procedure, observation, and a Probability model.
- 2.To inculcate ability to characterize functions of random variables
- 3.To familiarize the students with the methods to characterize stochastic processes with an emphasis on stationary random processes.
UNIT – I
The meaning of Probability – Introduction- the definitions – Probability and Induction – Causality versus Randomness.
The Axioms of Probability: Set theory – Probability Space – Conditional Probability. Repeated Trials: Combined Experiments – Bernoulli Trials – Bernoulli’s theorem and games of chance.
UNIT – II
The Concept of a Random Variable: Introduction – Distribution and Density functions-Specific Random Variables – Conditional Distributions – Asymptotic Approximations for Binomial Random variables.
Functions of One Random Variables: The Random Variable g(x) – The Distribution of g(x) – Mean and Variance – Moments – Characteristic Functions.
UNIT – III
Two Random Variables: Bivariate Distributions – One Function of Two Random Variables – Two Function of Two Random Variables – Joint Moments – Joint Characteristic Functions – Conditional Distributions – Conditional Excepted Values.
UNIT – IV
Random Processes – Definitions – Basic concepts and examples – Stationarity and ergodicity – Second order processes – Weakly stationary processes – Covariance functions and their properties – Spectral representation Weiner – Kintchine theorem.
UNIT –V
Linear Operations: Gaussian processes – Poisson Processes – Low pass and Band pass noise representations.
Suggested Reading:
1.Papoulis: Probability, Random Variables and Stochastic Processes, 4th Edition Tata McGraw Hill, 2002
- 2.T.Veerarajan, “Probability, Statistics and Random Process”, 3rd Edition Tata McGraw Hill
- 3.Peyton Peebles: Probability, Random Variables and Random Signal Principles, Fourth Edition, Tata McGraw Hill
- 4.H.Stark and J Woods: Probability, Random Processes and Estimation Theory for Engineers, Prentice