EE505 -- Probability and Random Processes
Course Information, Fall 2015
- Web pages under construction
Course Hours: M 6-8:50
Location: EEB 045
Mari Ostendorf (mo at ee)
Office: EEB Rm 215D (inside 215, door by 205)
Office Hours: Mon 4:30-5:30, other TBD
Ji He (luanyi at uw) and Hao Cheng (chenghao at uw)
Office Hours: TBD
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.
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.
Probability and Random Processes for Electrical Engineering, A. Leon-Garcia (3rd edition)
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)
Class Assignments: 10%
Midterm: 30% (Nov 9)
Final Exam: 40% (Dec 12, 4:30-6:20pm, EEB 045)
More Information and resources:
This page is maintained by Mari Ostendorf (ostendor@uw).