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Course Discription |
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Review of probability and random variables. Moments and characteristic function. Random vectors. Random processes: definition of a random process, specifying a random process, examples of random processes, stationary and wide-sense stationary processes, cyclo-stationary processes, mean and autocorrelation functions, power spectral density, time averages and ergodicity, response of linear systems to random signals. Optimum linear systems. Markov chains. Introduction to queueing theory. Poisson processes. Brownian motion process. Introduction to stochastic geometry. |