Electrical and Comp Engineerng
EECE 7204: Applied Probability and Stochastic Processes
Lecture - 4 credits
- Covers the fundamentals of probabilistic treatment and the concept of random processes, which are essential for many engineering disciplines and data analysis in general.
- Includes the basic laws of probability, random variables and their functions, probability density and cumulative distributions, statistical averages, bounds on probability, and the central limit theorem.
- Outlines basic principles of statistics, including estimation of probability, confidence intervals, and order statistics.
- Provides an overview of detection and estimation problems, including maximum likelihood and Bayesian principles, Cramer-Rao bound, linear estimators, and hypothesis testing.
- Studies random sequences, with notions of convergence, laws of large numbers, and examples of Markov chains.
- Defines random processes, along with the concepts of stationarity, ergodicity, autocorrelation and power spectral density, and filtering operations.
Covers the fundamentals of probabilistic treatment and the concept of random processes, which are essential for many engineering disciplines and data analysis in general. Show more.