J4 ›› 2009, Vol. 36 ›› Issue (6): 1015-1020.

• Original Articles • Previous Articles     Next Articles

Recursive total least lp-norm algorithm for adaptive IIR filtering in α stable noise environments

ZHANG Bin1,2;FENG Da-zheng1;LIU Jian-qiang1
  

  1. (1. Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an  710071, China
    2. The Telecommunication Inst., Air Force Eng. Univ., Xi'an  710077, China)
  • Received:2008-09-05 Online:2009-12-20 Published:2010-01-20
  • Contact: ZHANG Bin E-mail:zhangbin5037@163.com

Abstract:

When both the input and the output of a linear system are corrupted by α stable noises, the classical least mean lp-norm (LMP) algorithms usually provide a biased solution and the total least mean lp-norm (TLMP) algorithms suffer from slow convergence. The aim of this paper is to develop a recursive total least lp-norm (IIR_RTLP) algorithm for adaptive IIR filtering with noisy data. The proposed IIR_RTLP algorithm makes the expectation of lp-norm of the error be minimized when both the input and the output are corrupted by α stable noises. In ordor to trace the time-varing system and increase the speed of convergence, the IIR_RTLP algorithm recursively updates the adaptive filter coefficients on the basis of the matrix inversion lemma and the power iteration. Simulation results show that the IIR_RTLP algorithm can lead to faster convergence and a smaller system error than the existing TLMP algorithms for adaptive IIR filtering.

Key words: stable noises, adaptive filtes, IIR system, recursive total least lp-norm, power iteration

CLC Number: 

  • TN911.72