Probability and Random Processes (Units 1,2 , 4 and 5) Scanned Lecture Notes

  • 2Jan
  • 2015
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    Anna University , Chennai
    Department of B.E-Electronics and Communication Engg
    Probability and Random Processes
    Units 1 , 2 , 4 and 5 Scanned Lecture Notes

    Content :
    Unit 1
    Sample space

    1.Trial and event
    Exhaustive events
    Mutually exclusive events
    Favourable events
    Equally likely events
    Independent events
    Mathematical defn. of probability
    Axiomatic definition of probability
    Openations on sets
    Properties of sets
    Complementary laws
    Theorems on probability
    Theorem 1
    Theorem 2
    Theorem 3
    Theorem 4
    Theorem 5
    Theorem 6
    Theorem 7
    Conditional probability
    Problems on conditional Probability
    Baye’s theorem
    Problems on Baye’s theorem
    1.Discrete random variable
    2.Probability mass function (prnf)
    Probability distribution
    2. Continuous random variable
    Probability density function (pdf)
    Expectation of X:-E:- (mean)
    Cumulative distribution function (df)
    Properties of the cumulative distribution function
    Problems on continuous random variable
    Moment generating function MGF
    Moment generating function about origin
    Properties of MGF

    Unit 2
    Standard distributions
    Discrete distributions
    Continuous distribution
    1.Binomial distribution
    Poisson distribution
    Moment generating function of poisson distribution
    Geometric distribution
    Mean and variance of geometric distribution
    Establish the  memory loss property of Geometric distribution
    Continuous distribution 
    Uniform distribution (or) Rectangular distribution
    Gamma distribution
    Additive property of Gamma distribution 

    Unit IV
    Classification of random process
    Introduction 
    Definition
    Stationary Process
    Average values of Random process
    Strict sense stationary process ( SSS process )
    Ergodic process
    Definition
    Marcov Process
    Marcov chain
    Transistion probability matrix:- (TPM)
    Chapman Kolmogoron equation:- (CKE)
    Initial probability dist 
    Normal process
    Poisson process
    Definition
    Postulates
    1.Independents
    2.Homogeneity in time 
    3.Regularity
    Theorem
    Properties of poisson process
    Additive property

    Unit V
    Correlation and Spectral Densities 
    Auto correlation and its properties
    Properties of auto correlation fn.R©
    Power spectral density function

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