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.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_nylv93on

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

Mathematics

Probability theory: Topics in probability theory

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