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: