ECE 516 - Adaptive Digital Filters

Description: Credit 4. Properties of signals; optimal filters, Wiener and Kalman filters; signal modeling,

adaptive filters, channel equalizing, echo canceling, noise canceling, and linear prediction; filter properties.

Prerequisites: ECE 317 and ECE 341


  • Discrete time random signals and properties
  • Signal modeling and forward and backward prediction
  • Wiener filter and properties
  • Linear Prediction and algorithms
  • Kalman filter and it extensions
  • Smoothing filters
  • Adaptive filters including LMS and RLS algorithms
  • Adaptive filter applications such as to: channel equalizing, echo canceling, etc.
  • Adaptive filter convergence properties
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