MATH 466

Fall 2023 All Classes

All Classes

Applied Random Processes

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Credit: 3 OR 4 hours.

Systematic discussion of discrete-time Markov chains, continuous-time Markov chains and discrete-time martingales. Topics include strong Markov properties, recurrence and transience, invariant distributions, convergence and ergodicity, time reversal, Q-matrices, holding time, forward and backward equations, martingales and potential theory, queuing networks, Markov decision processes, Markov Chain and Monte Carlo techniques. Unlike other campus stochastic processes courses, this course will emphasize the fundamental mathematical constructions underlying the theory of Markov chains, such as Laplace operators, martingales, and harmonic functions.

3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: MATH 241, MATH 416, and MATH 461. Priority registration will be given to students in the Mathematics + Data Science major.

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MATH 466 class schedule data for fall 2023
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	76790	Lecture-Discussion	D13	11:00AM -11:50AM	MWF	307 David Kinley Hall	Song, R	Part of Term: 1 Date Range: 08/21/23-12/06/23 Credit: 3 hours Section Info: During early registration, this class is restricted to majors specifically requiring the course. More information is available here: https://go.math.illinois.edu/registration
	76794	Lecture-Discussion	D14	11:00AM -11:50AM	MWF	307 David Kinley Hall	Song, R	Part of Term: 1 Date Range: 08/21/23-12/06/23 Credit: 4 hours Section Info: Graduate students requesting the 4 credit hour section must first register for the 3 hour section. If the instructor is willing to offer extra work to graduate students for the 4-hour section, students can fill out the request form between the first day of the semester and the 8th week of the semester at this link: https://go.math.illinois.edu/3to4credit