The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Implementation of Adaptive Noise Canceller with Instantaneous Gain

순시 이득을 이용한 적응잡음제거기 구현

  • 이재균 (대구대학교 정보통신공학과) ;
  • 김춘식 (대구대학교 정보통신공학과) ;
  • 이채욱 (대구대학교 정보통신공학과)
  • Published : 2009.08.31
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Abstract

The Least Mean Square (LMS) algorithm is often used to restore signal corrupted by additive noise. A major defect of this algorithm is that the excess Mean Square Error (EMSE) increases linearly according to speech signal power. This result reduces the efficiency of performance significantly due to the large EMSE around the optimum value. Choosing a small step size solves this defect but causes a slow rate of convergence. The step size must be optimized to satisfy a fast rate of convergence and minimize EMSE. In this paper, the Instantaneous Gain Control (IGC) algorithm is proposed to deal with the situation as it exists in speech signals. Simulations were carried out using a real speech signal combined with Gaussian white noise. Results demonstrate the superiority of the proposed IGC algorithm over the LMS algorithm in rate of convergence, noise reduction and EMSE.

LMS알고리즘은 잡음이 섞인 신호로부터 원 신호를 복원하는데 자주 사용된다. 이 LMS알고리즘의 주된 결점은 음성 신호 파워에 따라 선형적으로 EMSE(Excess Mean Square Error)가 증가한다. 그 결과 최적의 값에서 큰 EMSE 때문에 성능의 효율성이 떨어진다. 이러한 결점은 적은 스텝사이즈를 선택함으로서 해결 할 수 있지만, 수렴율이 늦어지는 단점이 있어, 빠른 수렴율과 낮은 EMSE를 동시에 만족할 수 있는 값이 필요하다. 본 논문에서는 IGC(lnstantaneous Gain Control) 알고리즘을 음성신호가 존재하는 경우에서 제안한다. 시뮬레이션은 음성신호와 가우시안 잡음을 이용하여 수행하였고, 수렴율, 잡음제거, 그리고 EMSE에서 LMS알고리즘보다 IGC알고리즘이 우수하다는 것을 보인다.

Keywords

References

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