ENPM600

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.

Past Semesters

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During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.28 between 121 students*

ENPM600 Grade Distribution+-05101520253035404550556065% of studentsABCDFWother
A-: 21.49%
A: 25.62%
A+: 15.7%
B-: 3.31%
B: 12.4%
B+: 9.92%
C: 0.83%
F: 0.83%
W: 9.09%
other: 0.83%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.