MATH 588 - Stochastic Analysis
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Description
Hours: Three hours lecture per week Prerequisites: Admission to the Computer Science or Mathematics Graduate Program Topics include: Brownian motion, stochastic integrals, conditional expectation, Kolmogorv's Theorem, applications of Lebesgue Dominated Convergence Theorem. Introduction to Stochastic Differential Equations will be given.
Units: 3.00
Grading: Letter Grade
Session | Section | Class # | Type | Days | Time | Location | Instructor | Course Details [Key] |
---|---|---|---|---|---|---|---|---|
E1 | 1 | 2637 | LEC | T | 6:00 PM - 9:00 PM | Bell Tower 1688 | Jorge Garcia |
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