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12832 (v.2) Probability Theory and Random Processes 303
Area: School of Electrical and Computer Engineering Contact Hours: 4.0 Credits: 25.0 Lecture: 1 x 3 Hours Weekly Tutorial: 1 x 1 Hours Weekly Prerequisite(s): 12708 (v.2) Linear Systems 201 or any previous version
OR
302502 (v.1) Signal Processing 204 or any previous version
AND
12709 (v.2) Mathematics 277 or any previous version
OR
302980 (v.1) Mathematics 275 or any previous version
Axioms of probability theory. Probability measures. Conditional probability and statistical independence. Random variables. Probability density and distribution functions. Expectation and moment generating functions. Random processes. Stationarity. Correlation functions and power spectra. Wiener-Kinchin relations, response of linear systems. Statistical models. Methods of estimation. Confidence intervals and testing. Finite Markov chains. Decision theory. Applications of probability theory and stochastic processes in engineering.
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