A normalized LMF (XE-NLMF) algorithm with variable data-reusing

  • Authors:

  • Sung Jun Ban;Hyeonwoo Cho;Jae Jin Jeong;Sang Woo Kim

  • Affiliations:

  • Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, Korea;Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, Korea;Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, Korea;Division of Electrical and Computer Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, Korea

  • Venue:
  • ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
  • Year:
  • 2009

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Abstract

The normalized least-mean-fourth (XE-NLMF) algorithm has a faster convergence rate and lower misalignment performance than the normalized least-mean-squares (NLMS) algorithm in sub-Gaussian noise environments. However, the XENLMF algorithm shows convergence performance degradation in highly correlated input signals. To overcome the problem, we propose an XE-NLMF algorithm with variable data-reusing. Through computer simulations, we confirmed that the proposed algorithm has a better convergence performance than the conventional XE-NLMF algorithm for colored input signals.