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Conventional RLS Adaptive Filter

  • Paulo Sergio Ramirez
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 694)

Abstract

Least-squares algorithms aim at the minimization of the sum of the squares of the difference between the desired signal and the model filter output [1]–[2]. When new samples of the incoming signals are received at every iteration, the solution for the least-squares problem can be computed in recursive form resulting in the recursive least-squares (RLS) algorithms. The conventional version of these algorithms will be the topic of the present chapter.

Keywords

Input Signal Adaptive Filter Autocorrelation Matrix Optimal Coefficient Eigenvalue Spread 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Paulo Sergio Ramirez
    • 1
  1. 1.Federal University of Rio de JaneiroRio de JaneiroBrazil

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