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Probability and Random Processes

An introduction to probabilistic description (via the probability density function or distribution function) and statistical description (via the ensemble average, variance, etc.) of random signals as applied to the analysis of linear systems. Other topics include conditional probability, statistical independence, correlation, sampling theory, confidence intervals, hypothesis testing, stationary and ergodic processes, auto-correlation and cross-correlation functions, spectral density, and their interconnections.

Pre Requisites: Pre-Req: ENGIN 321

Offered in:

2018 Spring

Section Class Number Schedule/Time Instructor Location
01 8993 TuTh
9:30 - 10:45 am
Rahaim,Michael B S04-0073
Session: Regular
Class Dates: 01/22/2018 - 05/09/2018
Capacity: 36
Enrolled: 23
Status: Open
Credits: 3/3
Class Notes:
Pre Requisites: Pre-Req: ENGIN 321
Course Attributes: