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 |
2023-01-05 - 2023-04-12
MWF 10:00 - 10:50 (VVC 2-210)
Exam: 2023-04-19 @ 14:00 - 17:00 (VVC 2-210)
|
Primary Instructor: Chintha Tellambura
|
Section | Capacity | Dates + Times | Instructor(s) |
---|---|---|---|
SEMINAR J11
(40731) |
90 |
2023-01-05 - 2023-04-12
M 12:00 - 12:50 (NRE 1-003)
|
Primary Instructor: Chintha Tellambura
|