Introduction to Probability and Random Processes

Catalog description

This course is an introduction to probability and stochastic (random) processes for electrical engineering students. The course begins with an introduction to fundamental probability concepts, such as set theory, conditioning, independence, and counting methods. Random variables, such as binomial, uniform, and Gaussian, and their distributions are then introduced to model the outcomes of experiments with countable or measurable quantities. Foundational statistical concepts are covered through examining the sample mean and variance estimators, the central limit theorem, and law of large numbers. Random processes are introduced to model uncertainty in electrical signals, noise, and processing by linear filters. Examples are drawn from signal processing, communications, reliability, and engineering decision-making.