Math 286 (Driver, Spring 2008) Introduction to Stochastic Differential Equations
TA: There will be no TA for this course.
Meeting times: Lectures are on MWF 11:00a - 11:50a in AP&M 6218.
Textbook: Introduction to
Stochastic Integration, K. L. Chung and R. J. Williams, 2nd edition. There may also be some extra notes which will be
distributed on this web-page at "Lecture Notes."
Homework: There will be a few home
works throughout the quarter.
Description: Stochastic differential equations (SDE) can be used to model a variety of random dynamic phenomena in the physical, biological, engineering and social sciences. Solutions of these equations are often Markov diffusion processes. Because of this SDE theory has strong links to the classical theory of partial differential equations (PDE).
Stochastic differential equations arise in modeling a variety of random dynamic phenomena in the physical, biological, engineering and social sciences. Solutions of these equations are often diffusion processes and hence are connected to the subject of partial differential equations. This course will present the basic theory of stochastic differential equations and provide examples of its application.
RECOMMENDED ADDITIONAL REFERENCES:
Last modified on Tuesday, 25 March 2008 10:35 AM.