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ECEN 5612 - Noise and Random Processes

Catalog Data ECEN 5612 (3). Noise and Random Processes. Review of probability theory; convergence and probability bounds; multivariable normal theory; sequences of random variables and stochastic processes; Bernoulli and Poisson processes; wide-sense stationary processes; correlation functions and power spectra. Also includes linear systems with random inputs and Gauss-Markov processes; first- and second-order properties of ARMA processes; Markov chains.
Credits and Design 3 credit hours. Elective course.
Prerequisite(s) ECEN 3300, Linear Systems
Recommended Prerequisite(s) ECEN 3810, Introduction to Probability
Textbook Course notes.


  1. Probability, Random Variables, and Stochastic Processes, A. Papoulis, McGraw Hill.
  2. Probability Theory, R.M. Gray.
Course Objectives Establish the theoretical foundations of probability and apply it to problems in signal processing and communications.
Topics Covered
  1. Probability.
  2. Multivariate normal theory.
  3. Bernoulli and Poisson random processes.
  4. Correlation and power spectra.
  5. ARMA time series.
  6. Markov chains.

Last revised: 08-02-11, PM, ARP.