IC566: Random Signals and Random Processes (Spring 2018)
Instructor:
Kyung-Joon Park (kjp@, x6314, and E3-513)
Office hours: Right after class or by appointment
Class hour and classroom:
MTh 13:30-15:00 pm, E3-113
Textbooks:
- Introduction to Probability, Dimitri P. Bertsekas and John N. Tsitsiklis, Athena Scientific, 2nd edition, 2008
Course Description:
This will be an introductory graduate level course on probability and random processes.
The classes will have three phases:
First, we will begin with the review of undergraduate level probability and random variables.
Second, we will proceed to cover the basic concepts and engineering examples of discrete and continuous random processes, such as Bernoulli, Poisson, and Markov.
Last, we will apply our understanding of probabilistic models to detection and estimation problems of random signals.
Grading policies:
Homework 30%, Midterm exam 30%, Final exam 40%
Announcement:
Lectures:
- [Feb. 26] Probability models and axioms
- [Mar. 5] Conditioning and Bayes rule
- [Mar. 8] Independence
- [Mar. 12] Counting
- [Mar. 15] Discrete random variables; probability mass functions; expectations
- [Mar. 19] (Class begins at noon) Discrete random variable examples; joint PMFs & Multiple discrete random variables (regular + makeup class)
- [Mar. 22] No class (ICT Convergence Korea 2018)
- [Mar. 26] Continuous random variables; Multiple continuous random variables
- [Mar. 29] No class
- [Apr. 2] (Class begins at 1 pm) Multiple continuous random variables; Continuous Bayes rule; derived distributions (regular + makeup class)
- [Apr. 5] (Class begins at noon) Convolution; covariance and correlation; Iterated expectations; sum of a random number of random variables (regular + makeup class)
- [Apr. 9 & 12] No class (CPS Week 2018)
- [Apr. 16] Midterm exam
- [Apr. 19] Bernoulli process (makeup class)
- [Apr. 23] (Class begins at noon) Poisson process – I
- [Apr. 26] No class (미래통신기술 워크샵)
- [Apr. 30] Poisson process – II
- [May 3] Markov chains – I
- [May 7] No class (national holiday)
- [May 10] Markov chains – II
- [May 14] Markov chains – III
- [May 17] Weak law of large numbers
- [May 21] Central limit theorem
- [May 24] No class (ISET 2018)
- [May 28] Bayesian statistical inference – I
- [May 31] Bayesian statistical inference – II
- [June 4] Classical inference – I
- [June 7] Classical inference – II
- [June 11] Final exam