Research about Adjusted Step Size NLMS Algorithm Using SNR

신호 대 잡음비를 이용한 Adjusted Step Size NLMS알고리즘에 관한 연구

  • Published : 2008.04.30

Abstract

In this paper, we proposed an algorithm for adaptive noise cancellation (ANC) using the variable step size normalized least mean square (VSSNLMS) in real-time automobile environment. As a basic algorithm for ANC, the LMS algorithm has been used for its simplicity. However, the LMS algorithm has problems of both convergence speed and estimation accuracy in real-time environment. In order to solve these problems, the VSSLMS algorithm for ANC is considered in nonstationary environment. By computer simulation using real-time data acquisition system(USB 6009), VSSNLMS algorithm turns out to be more effective than the LMS algorithm in both convergence speed and estimation accuracy.

본 논문에서는 실시간 자동차 환경에서 VSSNLMS(variable step size normalized least mean square)를 이용하여 적응 잡음 제거 알고리즘을 제안한다. 기본적인 ANC(adaptive noise canceller)알고리즘인 LMS알고리즘은 알고리즘의 간단성 때문에 가장 많이 사용되고 있다. 그러나 LMS알고리즘은 수렴율과 실시간 환경에서의 정확성 사이에서 문제를 가지고 있다. 이러한 문제를 풀기 위해, 비정장성 환경에서 잡음제거를 위해 VSSLMS알고리즘이 사용된다. 본 논문에서 실시간 데이터 입력 시스템을 사용하여 컴퓨터 시뮬레이션 함으로써, VSSLMS알고리즘이 LMS알고리즘에 비해 수렴율과 정확성 이 모두에 더 효율적이라는 것을 입증한다.

Keywords

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