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A New Quantized Input RLS, QI-RLS, Algorithm

  • A. Amiri
  • M. Fathy
  • M. Amintoosi
  • H. Sadoghi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4707)

Abstract

Several modified RLS algorithms are studied in order to improve the rate of convergence, increase the tracking performance and reduce the computational cost of the regular RLS algorithm. . In this paper a new quantized input RLS, QI-RLS algorithm is introduced. The proposed algorithm is a modification of an existing method, namely, CRLS, and uses a new quantization function for clipping the input signal. We showed mathematically the convergence of the QI-RLS filter weights to the optimum Wiener filter weights. Also, we proved that the proposed algorithm has better tracking than the conventional RLS algorithm. We discuss the conditions which one have to consider so that he can get better performance of QI-RLS against the CRLS and standard RLS algorithms. The results of simulations confirm the presented analysis.

Keywords

Adaptive Filter Recursive Least Square (RLS) Weiner Optimum Weights Tracking 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • A. Amiri
    • 1
    • 2
  • M. Fathy
    • 2
  • M. Amintoosi
    • 2
    • 3
  • H. Sadoghi
    • 3
  1. 1.Islamic Azad University-Zanjan Branch 
  2. 2.Faculty of Computer Engineering, Iran University of Science and Technology 
  3. 3.Faculty of Engineering, Tarbiat Moallem University of SabzevarIran

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