Probability and Random Processes for Electrical Engineering: Leon-Garcia, A (Required)
Applied Stochastic Processes: Lefebvre, M  (Recommended)
An Introduction to Stochastic Processes: Kao, A (Recommended)

  Chapters will be covered based upon topics outlined below

Lectures: This course will be an introduction to probability and random processes. The targeted audience will upper-level undergraduates and beginning graduate students in science, engineering, statistics, computer science and applied mathematics. By the end of the course, students would have acquired ample knowledge on how to make a transition from real problems to probability models and the relevance of probability theory to science and engineering practices. A selection of topics (with applications) from the following areas will be studied:

I.   Basic concepts of probability theory
II.  Random variables; Generating functions; Entropy; Multiple random variables
III. Random processes; Discrete, stationary and continuous-time random processes
IV. Analysis and processing of random signals; The Kalman filter
V.  Markov chains (discrete and continuous); Time reversible Markov chains
VI. Introduction to Queuing Theory; M/M/I, M/M/C and M/G/I systems; Burke's theorem..

We shall cover book chapters from Leon-Garcia and selected topics from Kao and Lefebvre. We shall allude to other topics (hand-outs to be provided when necessary) as may be required. Practical implementation of algorithms on computers using MATLAB will be encouraged. Students will be required to complete one term project.