Lecture
Random Vectors and Stochastic Models for Communications
Description
This lecture covers random vectors, stochastic models for communications, joint cumulative distribution function, joint probability density function, marginal probability density function, conditional probability density function, independence of random variables, linear functions of two random variables, covariance, characteristic function, conditional probability, and expectation.
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