ECE 534: Random Processes (Fall 2022)

Course Information

Homework

Submissions via gradescope

Past Webpages

Spring 2020

Notes

Lectures are heavily based on the notes by Prof. Srikant and the text by Prof. Hajek (Spring 2020 syllabus).

For in-class notes, please contact Yixuan.

Disclaimer: The in-class notes correspond to files shared by your classmates. Therefore, no correction of typos or of technical

parts will be performed. It is highly suggested that you attend lectures, take your own notes and use the posted in-class notes as

complementary material.

Lectures

Week 1 Probability Space Reading: Lecture 1 by Prof. Srikant, Section 1.1 by Prof. Hajek
Week 2 Conditional Probability and Independence, Random Variables, Measurability and Lebesgue Integration Reading: Lectures 2,3 by Prof. Srikant, Sections 1.2, 1.3, 1.5 by Prof. Hajek
Week 3 Basic Inequalities (Markov, Reverse Markov and Chebyshev), Fundamental Functions (Characteristic, Moment Generating and Probability Generating), Important Distributions (Part 1) Reading: Lectures 3,4 by Prof. Srikant, Sections 1.5, 1.6 by Prof. Hajek
Week 4 Important Distributions (Part 2), Jointly Distributed Random Variables, Functions of Random Variables, Jensen's Inequality (Part 1) Reading: Lectures 4-7 by Prof. Srikant, Sections 1.6, 1.8-1.11, 2.4 by Prof. Hajek

Exams

Midterm 1 Oct 11, in class
Midterm 2 Nov 15, in class