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Probability and Stochastic Processes for Engineers

Prerequisite: Undergraduate introduction to discrete and continuous probability. Axioms of probability; conditional probability and Bayes' rule; random variables, probability distributions and densities; functions of random variables; definition of stochastic process; stationary processes, correlation functions, and power spectral densities; stochastic processes and linear systems; estimation and optimum filtering. Applications in communication and control systems, signal processing, and detection and estimation.

Fall 2021

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Average GPA: 3.25 between 115 students

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