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 | Class times | Login to view Instructor(s) and Location |
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LECTURE A1
(46802) |
135 |
2024-09-03 - 2024-12-09 (TR)
08:00 - 09:20
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SEMINAR E11
(46803) |
135 |
2024-09-03 - 2024-12-09 (M)
08:00 - 08:50
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LECTURE B1
(70490) |
90 |
2025-01-06 - 2025-04-09 (MWF)
10:00 - 10:50
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Section | Capacity | Class times | Login to view Instructor(s) and Location |
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SEMINAR J11
(70491) |
90 |
2025-01-06 - 2025-04-09 (M)
12:00 - 12:50
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