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525.414 - Probability and Stochastic Processes for Engineers Course Homepage

Instructor Information

Robert Fry

Email: rfry@segmail.com
Work Phone: (410) 381-8740 x202
Home Phone: (410) 840-8175

Course Information

Course Description

This course provides a foundation in the theory and applications of probability and stochastic processes and an understanding of the mathematical techniques relating to random processes in the areas of signal processing, detection, estimation, and communication. Topics include the axioms of probability, random variables, and distribution functions, functions and sequences of random variables; stochastic processes; and representations of random processes.

Prerequisites

An undergraduate degree in electrical engineering.

Course Goal

The goal of this course is to develop a working knowledge in the student of basic concepts and methodologies in probability and statistics which can then be applied to practical scientific and engineering problems.

Course Objectives

  • The major objectives of this course include:

    • Understanding and have a working knoweldge of the basic axioms and identities of probability theory
    • Developing the ability to determine probability distributions and densities for transformed random variables
    • Ability to understand and apply basic statistical methods
    • Be able to apply the methods of stochastic processes to everyday problems

When This Course is Typically Offered

This course is typically offered during the Spring term.

Syllabus

Topics Covered

  • Course overview, meaning of probability, axioms of probability, conditional probability, Bayes' theorem
  • Bernoulli Random Trials, Asymptotic Theorems, Definition of an RV, CDF, PDF, Conditional CDF & PDF
  • Binomial Approximations, Poisson Approximation, Function of a random variable.
  • Mean, Variance, Moments, and Characteristic Functions
  • Bivariate Distributions and One function of two random variables,
  • Midterm Preparation and Review
  • Midterm and Introduction to two functions of two random variables.
  • Two functions of two random variables and Joint Moments.
  • Joint Characteristic Functions, Conditional Distributions, and Conditional means.
  • Mean Square Estimation, Parameter Estimation, and The Weak Law and Strong Law of Large Numbers.
  • Stochastic Processes
  • Stochastic Processes and Linear Systems
  • Power Spectral Densities
  • Final Exam (Comprehensive)

Student Assessment Criteria

Homework 25%
Discussion Forum Participation 20%
Midterm 25%
Final Exam 30%

Computer and Technical Requirements

This course assumes a working knowledge of calculus and a basic understanding of logic and Boolean algebra.

Participation Expectations

The course is broken up in 14 modules with one module assigned per week.  Associated with each module is a homework assignment.  In addition, there are 2 exams - Midterm and Final.  The final exam is comprehensive.  Also, a discussion question is posed each week.  It is expected that all students will participate every week in the discussion forum to discuss this and other questions.  The teacher also participates in this forum.

It is expected that students will work alone on both homework assignments and exams. 

Textbooks

Textbook information for this course is available online through the MBS Direct Virtual Bookstore.

Course Notes

There are notes for this course.

(Last Modified: 01-21-2009 at 12:06:58 PM)