Convergence Analysis of Adaptive L-Filter

적응 L-필터의 수렴성 해석

  • 김수용 (창신대학 항공메카트로닉스과) ;
  • 배성호 (동명대학교 의용공학과)
  • Published : 2009.09.30

Abstract

In this paper we analyze the convergence behavior of the recursive least rank (RLR) L-filter. The RLR L-filter is an order statistics filter, filter coefficients of which are the weights according to the order of magnitude of inputs. And RLR L-filter is a non-linear adaptive filter, that uses RLR algorithm for coefficient updating. The RLR algorithm is a non-linear adaptive algorithm based on rank estimates in Robust statistics. The mean and mean-squared convergence behavior of the RLR L-filter is examined with variable step-sizes. The RLR L-filter adapts the median filter type to the heavy-tailed distribution function of impulse noise, and adapts the average filter type to Gaussian noises.

본 논문에서는 순환최소순위(RLR) L-필터의 수렴성을 해석하였다. RLR L-필터는 순서통계필터로서 입력의 크기순서에 따른 가중치를 필터계수로 한다. 또한 RLR L-필터는 비선형 적응 필터로서 필터계수의 갱신을 위하여 RLR 알고리즘을 이용한다. RLR 알고리즘은 로버스트 통계학의 순위추정에 기초한 비선형 적응 알고리즘이다. 본 논문에서는 가변적인 스텝 크기를 적용하여 평균 및 평균제곱의 견지에서 수렴성을 해석하였다. RLRL-필터는 잡음의 분포함수가 두꺼운 꼬리 분포인 임펄스 잡음에 가까울수록 메디안 필터의 형태로 적응하며 가우시안 잡음의 경우 평균 필터의 형태로 적응한다.

Keywords

References

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