ECE 4110

Last Updated

  • Schedule of Classes - April 13, 2023 2:00PM EDT
  • Course Catalog - April 12, 2023 7:14PM EDT

ECE 4110
Random Signals in Communications and Signal Processing

Course information provided by the Courses of Study 2022-2023.

Introduction to models for random signals in discrete and continuous time; Markov chains, Poisson process, queuing processes, power spectral densities, Gaussian random process. Response of linear systems to random signals. Elements of estimation and inference as they arise in communications and digital signal processing systems.

When Offered Fall.

Prerequisites/Corequisites Prerequisite: ECE 2720, ECE 3100, and ECE 3250 or equivalents.

Outcomes
  • Knowledge of a variety of mathematical models for random phenomena.
  • Ability to classify models with respect to stationarity, Markov property, asymptotics, and more.
  • Ability to make optimal inferences and estimates with respect to such criteria as minimum error probability, and minimum mean square error.
  • Become aware of applications to communications, machine learning, statistical physics and more.
  • Response of linear systems to random process inputs (time permitting).

View Enrollment Information

Syllabi:

  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: ECE 5110

  • 4 Credits Graded

  •  9859 ECE 4110   LEC 001

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  • Instruction Mode: In Person

  •  9860 ECE 4110   DIS 201

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  • Instruction Mode: In Person