Lecture 10: Recursive Least Squares Estimation

Lecture 10 11 Applications of Recursive LS flltering 1. Adaptive noise canceller Single weight, dual-input adaptive noise canceller The fllter order is M = 1 thus the fllter output is y(n) = w(n)Tu(n) = w(n)u(n) Denoting P¡1(n) = ¾2(n), the Recursive Least Squares flltering algorithm can be rearranged as follows: RLS ................
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