Deterministic and probabilistic models. Basics of probability theory: random experiments, axioms of probability, conditional probability and independence. Discrete and continuous random variables: cumulative distribution and probability density functions, functions of a random variable, expected values, transform methods. Pairs of random variables: independence, joint cdf and pdf, conditional probability and expectation, functions of a pair of random variables, jointly Gaussian random variables. Sums of random variables: the central limit theorem; basic types of random processes, wide sense stationary processes, autocorrelation and crosscorrelation, power spectrum, white noise. Prerequisite: MATH 209. Credit may be obtained in only one of ECE 342 or E E 387.
Section  Capacity  Dates + Times  Instructor(s) 

LECTURE B1
(40730) 
90 
20230105  20230412
MWF 10:00  10:50 (VVC 2210)
Exam: 20230419 @ 14:00  17:00 (VVC 2210)

Primary Instructor: Chintha Tellambura

Section  Capacity  Dates + Times  Instructor(s) 

SEMINAR J11
(40731) 
90 
20230105  20230412
M 12:00  12:50 (NRE 1003)

Primary Instructor: Chintha Tellambura
