## EE505 -- Probability and Random Processes

### Course Information, Fall 2014

**Announcements:**

- Old exam solutions and formula sheets are posted
- Notify Prof. Ostendorf by 12/12 if there are grading errors.
- Exam info:
- Exam is cumulative with emphasis on second half, but you need to know the material in the first half to do the second half
- The exam will cover everything on the current syllabus, in HWs and in lectures except for random variable sequence convergence (7.4), estimation of random processes (10.4).
- Same format as midterm: closed book, 20 pages of notes, no electronics

**Course Hours: ** T,Th 4:00-5:50

**Location: **EEB 045

**Lecturers: **

**Mari Ostendorf** (mo at ee)

*Office:* EEB Rm 215D (inside 215, door by 205)

*Office Hours:* Mon 4:00-5:30, Thurs 6-6:30pm, other by appt.

**Yi Luan** (luanyi at uw)

*Office Hours: *Tues 2:30-4, Weds 10-11:20 (EEB atrium)

**Grader:** (yuankunl at uw) Yuankun Li

**Course description:**

Foundations for the engineering analysis of random processes: set theoretic fundamentals, basic axioms of probability models, conditional probabilities and independence, discrete and continuous random variables, multiple random variables, sequences of random variables, limit theorems, models of stochastic processes, noise, stationarity and ergodicity, Gaussian processes, power spectral densities.

**Prerequisite:** Understanding of basic probability (random variables, distributions, expectations) and linear systems; familiarity with Matlab programming.

**Course objectives:**

Students who complete this course should gain:

- knowledge of how to characterize stochastic processes and properties of important stochastic processes;
- experience in interpreting real world problems as random variables and stochastic processes;
- an understanding of the interaction of stochastic processes and linear systems;
- an introduction to a detection and estimation applications; and
- practical experience with simulation using MATLAB.

**Text:**

*Probability and Random Processes for Electrical Engineering,* A. Leon-Garcia (3rd edition)

**Reference Texts:**

*Probability, Random Variables, and Stochastic Processes,* by A. Papoulis and U. Pillai (4th edition);

*Probability, Random Processes and Estimation Theory for Engineers,* by H. Stark and J. Woods (2nd edition)

**Grading:**

*Homework:* 20%

*Class Assignments:* 10%

*Midterm:* 30% (Nov 6, 4-5:50pm, EEB 045)

*Final Exam:* 40% (Dec 12, 4:30-6:20pm, EEB 045)

More Information and resources:

This page is maintained by Mari Ostendorf (mo@ee).