ECE 5650

ECE 5650

Course information provided by the Courses of Study 2016-2017.

This course introduces fundamental theories and practical ideas in statistical signal processing and learning. Specific topics include Bayesian inference, Wiener and Kalman filters, predictions, graphical models, point estimation theory, maximum likelihood methods, moment methods, Cram´er-Rao bound, least squares and recursive least squares, supervised and unsupervised learning techniques.

When Offered Spring.

Prerequisites/Corequisites Prerequisite: ECE 3100 or ECE 3250.

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Syllabi: none
  •   Regular Academic Session. 

  • 4 Credits Graded

  • 17366 ECE 5650   LEC 001