ECE353: Introduction to Probability and Random Signals

Spring 2018
School of Electrical Engineering and Computer Science
Oregon State University

Course Information

Instructor:	Dr. Raviv Raich
Office:	Kelley Engineering Center 3009
Email:	* Kindly use this email address (and not the onid email address)
Classroom:	Learning Innovation Center (LINC) room 210
Time:	Tue./Thu. 2:00PM - 3:20PM
Office hours:	Thu. and Fri. 4:00PM-5:00PM

Grading TA

Grading TA:	HW 1: Shashini HW 2: TBD HW 3: TBD HW 4: TBD HW 5: TBD HW 6: TBD HW 7: TBD HW 8: TBD HW 9: TBD HW 10: TBD
TA Office hours:	Shashini De Silva (desilvas at oregonstate.edu) Mon 4.00pm - 5.00pm, Wed 9.00am - 10:00am@KEC Atrium Lai Phung (laith at oregonstate.edu) Tue. 4:00pm - 5:00pm, Fri 9.00am - 10:00am@ KEC Atrium

News

Class starts Tue. April 3, 2018.

Course Description

Introductory discrete and continuous probability concepts, single and multiple random variable distributions, expectation, introductory stochastic processes, correlation and power spectral density properties of random signals, random signals through linear filters.

Prerequisites

Junior standing in ECE 351 and (MTH 254 or MTH 254H).

Textbook

"Probabilistic Systems and Random Signals," by Abraham H Haddad, Prentice Hall 2006, ISBN-10: 0130094552

Topics

Chapter 1 - Introduction

What is Probability

Chapter 2 - Basic Probability

Set Theory and Events
Axioms of Probability
Conditional Probability and Independence
Total Probability and Bayes Rule

Chapter 3 - Single Random Variable

Definition of a Random Variable
Distribution and Density Functions

Chapter 4 - Function of a Random Variable and Expectations

Function of a Random Variable
Expectations
Moments, Mean, and Variance

Chapter 5 - Two Random Variables

Joint Distribution Function
Joint Probability Mass Function
Joint Probability Density Function
Independence
Gaussian Random Variables

Chapter 6 - Expectations and Functions

Expectations of Two Random Variables
Linear Estimation

Chapter 12 - Random Processes

Introduction to Random Processes
Distributions of Random Processes
Mean and Autocorrelation Function
Cross-Correlations

Policy

Academic dishonesty: evidence of academic dishonesty in ECE353 may result in a grade of "F" on the examination/assignment that involved cheating and/or an "F" in the course (for more details see http://ecampus.oregonstate.edu/services/proctoring/academichonesty.htm).
Assignment deadlines: late assignments (e.g., HW) will not be graded. You are responsible to make sure that we receive your assignment on time.
Communications: use a professional and respectful language for in-classroom communications and emails. I reserve the right to ignore emails that begin with 'Hey'.
Grading: if you have any issues with grading of an assignment or exam, contact me within a week from when the assignment was returned.
Registration: please work out any registration issue with the EECS academic advisors first. If you are transferring credit for a prerequisite do so with your EECS undergraduate academic advisor. I will not provide waivers for students who do not have the prerequisites for the class. This class is challenging even for those who have the prerequisites for the class. I will not allow students with schedule conflict to take the class. This class is challenging even for those who attend it regularly.
Office hours: between the TAs and I, we hold more than 6 different office hours per week and an additional weekly HW review session. If you need help, we will gladly provided it during these allocated time slots. I do not provide `private lessons'. I regard requests to hold personal office hours as disrespectful. If your success in this class is important and you feel that you need help, make an effort to show in one of the 6 (or more) office hours offered - it is the least you can do. In turn, we will do our best to help.
Classroom attendance and behavior: you are strongly encourage to attend classes regularly. I hold random quizzes on a weekly basis. Missing a class could mean missing the quiz and the associated credit. No remake quizzes will be offered. While in class, I ask for no laptop or cell-phone use (e.g., texting, surfing, talking).

Homework & Solutions

Homework is due Tuesday one week after it is assigned.

Homework 1: HW1, due Tuesday April 10, 2017.
Homework 1 solution: HW1 solution,
Homework 2: HW2, due Tuesday April 17, 2017.
Homework 2 solution: HW2 solution,
Homework 3: HW3, due Tuesday April 24, 2017. Hints
Homework 3 solution: HW3 solution,
Homework 4: HW4, due Tuesday May 1, 2017.
Homework 4 solution: HW4 solution,
Homework 5: HW5, due Tuesday May 8, 2017.
Homework 5 solution: HW5 solution,
Homework 6: HW6, due Tuesday May 15, 2017.
Homework 6 solution: HW6 solution,
Homework 7: HW7, due Tuesday May 22, 2017.
Homework 7 solution: HW7 solution,
Homework 8: HW8, due Tuesday May 29, 2017.
Homework 8 solution: HW8 solution,
Homework 9: HW9, due Tuesday June 5, 2017.
Homework 9 solution: HW9 solution,
Homework 10: HW10,
Homework 10 solution: HW10 solution,

Midterm1 solution: Midterm_1_Solution,
Midterm2 solution: Midterm_2_Solution,

Notice : Efforts on homework should be individual based on the material in class and in the book. Students that will get caught copying their solution from the solution manual, past solutions, or other students, will face disciplinary actions.

Grading Policy

The final grade for this class will be determined based on

Midterm 1:	25%
Midterm 2:	25%
Homework:	10%
Final:	40%

The final grade will be based on the total number of points accumulated at the end of the term

Exams

Midterm 1:	Tue May 01, 2017 (week 5) 2:00-3:20 (in class)
Midterm 2:	Tue May 22, 2017 (week 8) 2:00-3:20 (in class)
Final:	Mon June 11, 2017 2:00-3:50 (in class)

Accommodations for students with disabilities are determined and approved by Disability Access Services (DAS). If you, as a student, believe you are eligible for accommodations but have not obtained approval please contact DAS immediately at 541-737-4098 or at http://ds.oregonstate.edu. DAS notifies students and faculty members of approved academic accommodations and coordinates implementation of those accommodations. While not required, students and faculty members are encouraged to discuss details of the implementation of individual accommodations.