Fall 2019
General Course Information
Learning Objectives
By the time the students successfuly complete the course, they should be able to:
- 1. Explain the foundations of probability theory, random variables, and stochastic processes.
- 2. Formulate and analyze probabilistic models and methods for
electrical and computer engineering problems.
- 3. Make precise statements about probabilistic models.
Brief Course Description
- Probability theory
- Random variables
- Stochastic processes
- Examples from various applications.
Text
Prerequisites
- Undergraduate linear signals and systems.
- Undergraduate probability and statistics.
- An appreciation of rigor and abstract thinking.
Grading
- Homework due every 2 weeks: 10%
- Three exams: 30% each
- Project: none
Examples of applications
- Communication systems
- Manufacturing systems
- Internet
- Computer performance modeling
- Investment planning
Contact information
Professor Edwin K. P. Chong
- E-mail: (preferred mode)
- Phone: 970-491-XXXX
- Fax: 970-491-2249
Course web pages:
Professor Edwin K. P. Chong,
This document was last modified
July 01, 2022.