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UNIT 1 :
PROBABILITY :Definitions, sample, space & events, joint & conditional
probability, independent events.
UNIT 2 : RANDOM VARIABLES : Introduction, distribution & density
functions, discrete & continuous random variables, special distributions :
binominal, poisson, uniform, exponential, normal, rayleigh, conditional
distribution & density functions.
UNIT 3 : MULTIPLE RANDOM VARIABLES : Vector random variable, joint
distribution functions, joint probability density function, conditional
distribution & density functions. Statistical independence, distribution &
density function of sum of random variable, one function of two random
variable, two function of two random variable., linear transformation
UNIT 4 : OPERATION ON SINGLE & MULTIPLE RANDOM VARIABLES : Mean &
variance, moments, chebyshev’s inequality, Central limit theorem,
characteristic functions & moment generating function, covariance &
correlation coefficient of multiple random variable.
UNIT 5: STOCHASTIC PROCESSES : Introduction, random process
concept, stationary & independence, ergodicity, correlation, functions.
Gaussion Random Process, Transmission of Random process through linear
systems. Power spectral Density, Cross Spectral density,
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