Description

This course is designed to build on the knowledge of deterministic signals and systems by introducing stochastic signals and related systems to students. These class of signals and systems are particularly important in real-life settings where the assumption of determinism (i.e., absence of noise or uncertainty) is hardly ever met. To deal with uncertainty (or noise) in signals and to develop useful systems to analyze and process such noisy signals, understanding of the concepts in probability theory and statistics is mandatory. This course aims to accomplish that task.

Specifically, this course will equip students with the knowledge and skills required to understand and apply probabilistic models and tools for signal modelling and analysis. Further, in this course, we will introduce basic techniques and methods for estimation of parameter(s) from noisy signals. The students will learn how to characterize a “good estimator” and will design and apply such estimators in the context of standard signal processing problems e.g., prediction.
Course period01/09/202131/12/2021
Course levelMaster level
Course format5