A new quantized input RLS, QI-RLS, algorithm

  • Authors:

  • A. Amiri;M. Fathy;M. Amintoosi;H. Sadoghi

  • Affiliations:

  • Islamic Azad University-Zanjan and Faculty of Computer Engineering, Iran University of Science and Technology;Faculty of Computer Engineering, Iran University of Science and Technology;Faculty of Computer Engineering, Iran University of Science and Technology and Faculty of Engineering, Tarbiat Moallem University of Sabzevar, Iran;Faculty of Engineering, Tarbiat Moallem University of Sabzevar, Iran

  • Venue:
  • ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part III
  • Year:
  • 2007

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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.