BM1201 Transforms and Random Process Syllabus


BM1201 TRANSFORMS AND RANDOM PROCESSES 3 1 0 100

1. FOURIER TRANSFORMS: 9
Fourier transform pairs, Properties – Fourier Sine and Cosine transforms, Transforms of simple functions, Transforms of derivatives, Convolution integrals, Evaluation of integrals using Fourier Transform.

2. LAPLACE TRANSFORM: 9
Transforms of simple functions, Properties, Transforms of derivatives and integrals, Periodic functions, Convolution theorem, Inversion formula, Initial and Final value theorems,
Applications to solve ordinary differential equations.

3. PROBABILITY AND RANDOM VARIABLES: 8
Probability concepts, Random variables, Moments, Moment generating function, Binomial, Poisson, Geometric, Exponential, Gamma distributions, Functions of a random variable.

4. TWO DIMENSIONAL RANDOM VARIABLES: 8
Joint, Marginal and Conditional distributions, Covariance, Correlation and Regression.

5. RANDOM PROCESSES: 11
Classification, Stationary and Markov processes, Poisson Process – Properties, Pure Birth Process, Birth and Death Process, Markov Chain, Auto-correlation and Cross-correlation functions - Properties.

L = 45, T = 15, TOTAL: 60

TEXT BOOKS:
1. Kandasamy.P, Thilagavathy. K, Gunavathy.K, ‘Engineering Mathematics’ Vol.III S.Chand & Co.2002
2. Veerarajan.T, ‘Probability statistics and Random Processes’ Tata McGraw-Hill, Co, New Delhi.2002.

REFERENCES:
1. J. Medhi, ‘Stochastic Processes’, New Age International Publication, New Delhi (2nd Ed), 1994.
2. Peebles Jr., ‘Probability, Random Variables and Random Signal Principles’ McGraw-Hill Publishers.1987.
3. H.M. Taylor and S.Karlia ‘An Introduction to Stochastic Modeling’, Academic Press, Inc., 1984.
4. U.N.Bhat, ‘Elements of Applied Stochastic Processes’, John Wiley, New York, 1984.
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