Department of Electrical and Computer Engineering

University of Massachusetts/Amherst

** **

**ECE ****697SM:
Stochastic Methods for Dense Networks**

**Spring 2011**

**Overview**: This
course is a graduate-level introduction to stochastic methods in dense network
analysis. This course covers some interesting and useful tools in stochastic
analysis, and could be helpful in advancing students own research
projects. It is also useful to prepare students for their career in
broadening their knowledge scope into other than their own disciplines.
Although the content is advanced, the treatment is quite basic.
Familiarity with basic probability theory, linear algebra and ordinary
differential equations would suffice as prerequisite. There will be 6-8
homework sets, a mid term exam, and a term paper.

**Objectives: **Students
completing this course will gain substantial knowledge about stochastic
analysis tools in dense network analysis. The course is designed to help
students for their own research projects as well as to prepare them for the
future development.

**Prerequisites:** Familiarity
with basic probability theory, linear algebra and ordinary differential
equation.

**Instructor:** Weibo
Gong

** **Phone:
(413) 545-0384; email: gong@ecs.umass.edu

**Lectures:** Marcus
106-108 (studio A); Time TBD.

**Office Hours: **TBD

**Textbook: **Lecture
Notes

**References: **Handouts

**Grading policy**: Homework:
20%

** **Midterm
Exam: 30%

Term Paper: 50%

**Topics plan to cover:**