# ECE 534: Random Processes (Fall 2012)

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Maxim Raginsky (contact: `maxim [at] illinois [dot] edu`)

TA: Ehsan Shafieepoorfard (contact: `eh [dot] shafiee [at] gmail [dot] com`)

TTh 2:00-3:20, 135 Mechanical Engineering Building

### Announcements

- Office hours
- Instructor: Tuesdays, 3:30 pm to 5 pm, 162 CSL
- TA: Fridays, 10 am to 1 pm, 369 Everitt

- Probability Review Quiz will be on Wednesday Sep 19th, from 6 pm to 7:30 pm in 116 Roger Adams Lab; the Quiz will be closed-book, closed-notes, no calculators or other electronic devices allowed
- There will be no class on Oct 2 and Oct 4 because of the Allerton Conference. There will be a make-up lecture on Monday, Oct 1, from 3 pm to 4:50 pm in 165 Everitt
- Homework 2 will be due on Thursday, Oct 11
- Those of you who have registered after Homework 1 and the Probability Review Quiz solutions were posted, please contact the instructor and the TA to arrange for make-up assignments as soon as possible, otherwise you will get a grade of ZERO on both
- Starting with Homework 2, there will be 5 points of extra credit for anyone who typesets their homework using LaTeX
- Exam 1 will be on Wednesday, Oct 24, from 6 pm to 7:30 pm in 165 Everitt Lab; you will be allowed one sheet of notes, and the exam will be closed book otherwise; no calculators or other electronic devices allowed
- Exam 2 will be on Wednesday, Nov 28, from 6 pm to 7:30 pm in 165 Everitt Lab; you will be allowed two sheets of notes, and the exam will be closed book otherwise; no calculators or other electronic devices allowed
- Final Exam will be on Friday, Dec 14, from 7 pm to 10 pm in 135 Mechanical Engineering Building; you will be allowed three sheets of notes, and the exam will be closed book otherwise; no calculators or other electronic devices allowed

### About this class

ECE 534: Random Processes is a graduate-level course on random (stochastic) processes, which builds on a first-level (undergraduate) course on probability theory, such as ECE 313. It covers the basic concepts of random processes at a fairly rigorous level, and also discusses applications to communications, signal processing, control systems engineering, and computer science. To follow the course, in addition to basic notions of probability theory, students are expected to have some familiarity with the basic notions of sets, sequences, convergence, linear algebra, linear systems, and Fourier transforms.

### Useful links