EE 3330 -Probability and Random Signals, Summer 2017

Syllabus (pdf)

Prerequisites:                                                                                             Calculus and linear algebra.

Time and place: 1:00 pm -2:50 pm, Tuesday-Thursday, NH 109

Textbook:                                                                                                                               . Alberto Leon-Garcia, Probability and Random Processes for Electrical Engineering, Third Edition, Pearson, 2008.

Additional Reading:                                                                                        

[1] P. Z. Peebles, Probability, Random Variables and Random Signal Principles, 4th Edition, McGraw-Hill, 2000.
[2] A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes, Fourth Edition, McGraw-Hill, 2000.

 Instructor:                                     Dr. Ioannis Schizas,                                Office: NH 534,                                    Email: schizas@uta.edu

Office Hours: 3:00pm-4:00pm, Tuesday-Thursday or by appointment

GTA: Dheeral Bhole (email: dheeral.bhole@mavs.uta.edu)

GTA Hours: Wed and Fri, 13:00-16:00, NH 205

Grading:                                                                     Homeworks: 15%                                                                                                        Midterm I: 25 %                                                                                                                    Midterm II: 25 %                                                                                                            Final: 35%

CourseMaterial:                                                                                               -Introduction to basic probability concepts and combinatorics. (Lecture notes: #1,#2,#3)
-Conditional probability, independence, sequential experiments. (Lecture notes: #1)
-
Binomial and multinomial distributions. (Lecture notes: #1)
-Discrete random variables, probability mass functions, mean and variance; Important discrete random variables in engineering applications.
(Lecture notes: #1)

-Continuous random variables, probability density function, expected value and variance; The Gaussian distribution and engineering applications. (Lecture notes: #1,#2)
-Functions of random variables, conditional probability density functions; Markov and Chebyshev inequalities. (Lectures notes: #1)
-Two random variables, joint and marginal cumulative density function and probability density function; Discrete and continuous cases. (Lectures notes: #1)
-Joint moments; Correlation, covariance and conditional expectation. (Lectures notes: #1)
-Functions of two random variables and jointly Gaussian random variables.
(Lectures notes: #1,#2)
-Vector random variables.
(Lectures notes: #1)
-Expected value and covariance matrices of random vectors.                                                             -Introduction to parameter estimation.                                                                                               -Law of Large Numbers and Central Limit Theorem in engineering.  (Lecture Notes: #1)                                                                                                                                                        -Random processes basics. (Lecture Notes: #1)

Homework Assignments

Homework Assignment Assigned Due date
Assignment 1: (pdf) 06/08/2017 06/15/2017
Assignment 2: (pdf) 06/15/2017 06/22/2017
Assignment 3: (pdf) 06/22/2017 06/29/2017
Assignment 4: (pdf) 07/06/2017 07/18 /2017
Assignment 5: (pdf) 07/17/2017 07/24 /2017
Assignment 6: (pdf) 08/1/2017 08/10 /2017