Stochastic Processes
Course Description
The course is devoted to the statistical characterization of stochastic (random) processes, signals with uncertainty which have temporal evolution. Several aspects and classes of stochastic processes are of interest and studied such as stationary and ergodic processes. Characterization of the random processes in the frequency domain are discussed soe we can model several applications in Telecommunications and Computer Engineering.
Prerequisites
Knowledge of calculus, linear algebra and statistics is required.
Course Goal
To provide students with the concepts and the comprehension of random processes with time evolution as well as the application of such concepts in problems of discrete and continuous domains in Telecommunications and Computer Engineering.
Program / Syllabus
- Characterization of Stochastic Processes
- Types and Examples of Stochastic Processes
- Stationary and Ergodic Processes
- Markov Chains
- Spectral Analysis of Stochastic Processes
Textbooks
- Steven M. Kay, Intuitive Probability and Random Processes using MATLAB. Springer, 2006.
- Alberto Leon-Garcia, Probability and Random Processes for Electrical Engineering. Prentice Hall, 3rd edition, 2007.
- José Paulo de Almeida e Albuquerque, José Mauro Pedro Fortes and Weiler Alves Finamore, Probabilidade, Variáveis Aleatórias e Processos Estocásticos, Editora PUC-Rio, 2008.
Material (in Portuguese)
