Teaching

 

 
AMCS 143. Introduction to Probability and Statistics (3-0-0)
This course provides an elementary introduction to probability and statistics with applications. Topics include: basic probability models; combinatorics; random variables; discrete and continuous probability distributions; statistical estimation and testing; confidence intervals; and an introduction to linear regression.

AMCS 241/CS 241/EE 241 Probability and Random Processes (3-0-3)
Introduction to probability and random processes. Topics include probability axioms, sigma algebras, random vectors, expectation, probability distributions and densities, Poisson and Wiener processes, stationary processes, autocorrelation, spectral density, effects of filtering, linear least-squares estimation, and convergence of random sequences.
 
EE 244 Wireless Communications (3-0-3) Prerequisite: Preceded or accompanied by EE 241 and EE 242.
This course introduces fundamental technologies for wireless communications. It addresses the following topics: review of modulation techniques, wireless channel modeling, multiple access schemes, cellular communications, diversity techniques, equalization, channel coding, selected advanced topics such as CDMA, OFDM, Multiuser detection, space time coding, smart antenna, and software radio.
 
EE 252 Estimation, Filtering, and Detection (3-0-3) Prerequisite: EE 241.
Principles of estimation, linear filtering, and detection. Estimation: linear and nonlinear minimum mean squared error estimation and other strategies. Linear filtering: Wiener and Kalman filtering. Detection: simple, composite and binary and multiple hypotheses as well as Neyman-Pearson and Bayesian approaches.
 
Enrolled students can access course material through KAUST's Blackboard via http://blackboard.kaust.edu.sa.