中文

Journal of Applied Sciences ›› 2013, Vol. 31 ›› Issue (5): 475-480.doi: 10.3969/j.issn.0255-8297.2013.05.006

• Signal and Information Processing • Previous Articles     Next Articles

Variable Step-Size Convex Combination of LMS Adaptive Filtering: Algorithm and Analysis

MIAO Jun1,2, RUI Guo-sheng1, ZHANG Yang1   

  1. 1. Department of Electronic Information Engineering, Naval Aeronautical and Astronautical University,
    Yantai 264001, Shandong Province, China
    2. Graduate Students’ Brigade, Naval Aeronautical and Astronautical University, Yantai 264001,
    Shandong Province, China
  • Received:2011-09-17 Revised:2011-12-14 Online:2013-09-26 Published:2011-12-14

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Abstract: The existing variable step-size convex combination of LMS (VSCLMS) algorithm needs to predetermine the behavioral parameters. To avoid this, the paper proposes a new variable step-size adaptive filter with analytical minimization of the ensemble-averaged mean-square weight error. Instead of variable step-size parameters in the original VSCLMS, the proposed algorithm uses a constant step-size parameter derived based on steady-state MSWE minimization. Theoretical analysis and simulations show that the proposed algorithm has a better tracking performance in the presence of noise and in a time-varying and even non-stable environment. Besides, it converges fast and is stable in the convergence process, and is better in these aspects as compared with the original VSCLMS and CLMS algorithms.

Key words: adaptive filtering, CLMS, VSCLMS, variable step-size, convex combination

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