EE 520, Fall 2021

Random Processes

This is the course website for EE 520, Random Processes, Fall 2021 quarter.

Meeting time: Mon/Wed 4:40-6:30PM, FAB 150
Office hours: Mon/Wed 6:30-7:30PM (or by appointment), FAB 160-19

Course Description

The goal of this course is to provide a rigorous understanding of probability theory at the graduate level and an introduction to random processes and their applications. Topics include random vectors, fundamentals of estimation, modeling random sequences with linear systems, stationarity, Markov random sequences, and common random process models.

Textbook: In addition to the below lecture notes, the course will utilize the textbooks below.

Syllabus: The syllabus can be found here.

Communication: I will not use email for course communication. All written questions should be posted to the appropriate channel on the Slack workspace (see Homework 0).

Course Schedule

This course will practice a flipped classroom. You are responsible for reading the listed textbook sections and lecture notes before class on the specified day. Please post any questions you have to the course slack channel, and we will spend class time presenting a mini-lecture and working examples. The textbook has numerous worked problems, and I recommend working as many of them as you have time for.

Date Lecture Sections Notes Exercises Solutions
9/27 1 1.1 - 1.4 The Probability Model Exercises 1 Solutions 1
9/29 2 1.5 - 1.7 Conditional Probability & Combinatorics Exercises 2 Solutions 2
10/4 3 2.1 - 2.4 Discrete Random Variables & Expectation Exercises 3 Solutions 3
10/6 4 2.4, 3.4, 3.5 Conditional Expectation Exercises 4 Solutions 4
10/11 5 4.1 - 4.3 Continuous Random Variables, Detection Theory Primer Exercises 5 Solutions 5
10/13 6 4.4, 5.1 The Cumulative Distribution Function Exercises 6 Solutions 6
10/18 7 5.2 - 5.5 Transformations of Random Variables Exercises 7 Solutions 7
10/20 8 7.1 - 7.5 Bivariate Random Variables Exercises 8 Solutions 8
10/25 9 — (catch up)    
10/27 10 2.4, 3.3, 4.5, 5.6 Concentration of Random Variables    
11/1 11 8.4 - 8.6 Estimation of Random Variables Exercises 10 Solutions 10
11/3 — Midterm Exam      
11/8 12 8.1 - 8.3 Random Vectors and Matrices Exercises 11 Solutions 11
11/10 13 9.1 - 9.5 Gaussian Random Vectors Exercises 12 Solutions 12
11/15 14 10.1 - 10.4 Random Processes Exercises 13 Solutions 13
11/17 15 10.5 - 10.8 Filtering Random Processes Exercises 14 Solutions 14
11/22 16 11.1 - 11.4 Counting Processes Exercises 15 Solutions 15
11/24 17 — no class (Thanksgiving)    
11/29 18 12.1 - 12.5 Markov Chains Exercises 16 Solutions 16
12/1 19 — (special topic)    

Resources