ECE 8702: Statistical Signal Processing

Course Description

This is an advanced course on probability, random signals, and stochastic process, and will cover

  • Probability and Random Variables: discrete and continuous random variables, functions and transformations of random variables, and conditional and joint distributions.

  • Random Processes: correlation and spectral analysis, the Gaussian process and the response of linear systems to random processes.

  • Important Random Processes: Poisson process, Markov chain, random walk, Wiener process, and Brownian motion.

  • Statistics: mean square estimation, parameter estimation, Baysian estimation.

Prerequisite: An introductory course on Probability, Random Variables, and Stochastic Processes is required.

Learning objectives

Students are exposed to the following topics:

  • Basic Probability: Events and Axioms

  • Discrete Random Variables

  • Continuous Random Variables

    Examples of continuous distributions
  • Central Limit Theorem

  • Estimation

Course Information

See the information in the links on the left.