• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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• pp.245-246
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• 2008

The Correlation FXLMS (Co-FXLMS) algorithm was developed to improve the control performance. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Modified Co-FXLMS is presented in comparison with that of the CO-FXLMS algorithm. Simulation results show that active noise control using Modified Co-FXLMS is effective to control performance of algorithm and prevent divergence.

• 한국소음진동공학회논문집
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• 제18권3호
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• pp.284-292
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• 2008

The active control technique mostly uses the least-mean-square(LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS(FXLMS) algorithm is applied to an active noise control(ANC) system. However, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation and experimental results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.598-603
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• 2007

The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.737-742
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• 2007

The method of the reducing duct noise can be classified by passive and active control techniques. However, passive control has a limited effect of noise reduction at low frequencies (below 500Hz) and is limited by the space. On the other hand, active control can overcome these passive control limitations. The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, the convergence performance of the LMS algorithm decreases slightly so it may delay the convergence time when the FXLMS algorithm is applied to the active control of duct noise. Thus the Co-FXLMS algorithm was developed to improve the control performance in order to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing duct noise.

• 전기학회논문지
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• 제61권10호
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• pp.1489-1495
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• 2012

In this study, the active noise control experiment has been performed using induction motor noises. While the noises were measured, a induction motor was operated in different speed. For the simulation of ANC(Active Noise Control), test-bed is composed a multi-channel ANC system was constructed. In order to compare the control performance, we performed noise reduction simulations of ANC by Co-FXLMS algorithm and FXLMS algorithm. Through the simulation results, we confirmed that convergence performance and noise decrease effect of the proposed Co-FXLMS algorithm have been improved from existing FXLMS algorithm.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 춘계학술대회 논문집
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• pp.39-40
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• 2007

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 추계학술대회 논문집
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• pp.251-252
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• 2007

• 전자공학회논문지T
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• 제35T권2호
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• pp.48-55
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• 1998

광대역 소음의 능동소음제어(Active Noise Control, ANC)에 사용되는 Filtered-X Least Mean Aquares(FXLMS) 알고리즘의 주 결점은 제어 알고리즘의 입력으로 사용되는 필터링된 기준신호가 상관되어 입력신호의 자기상관행렬이 큰 고유치비를 갖게 됨으로써 수렴속도가 느려지는 것이다. 이 상관은 그 원인이 기준센서 신호의 자기상관 때문이거나, 기준신호가 오차경로로 필터링되어서 나타난다. Recursive Least Squares(RLS)와 같은 빠른 수렴속도를 갖는 적응 알고리즘이 존재하지만, 이들 알고리즘은 실 계의 구현을 위해 많은 계산을 필요로 하거나, 각 샘플마다 제어기의 최적화가 필요한데, 이는 매우 심각한 제한조건이다. 본 논문에서는 빠른 수렴의 속도를 갖으면서 FXLMS와 근사한 연산량을 갖는 제어알고리즘을 제안한다. 이 알고리즘은 수렴속도를 느리게 하는 상관성을 줄이기 위해 이산 Walsh 변환을 사용하는 변환영역 FXLMS이다. 제안한 알고리즘을 광대역 능동소음제어 시스템에 적용, 모의시험한 결과 FXLMS의 문제점인 고유치비가 약 1/40으로 줄어드는 성능 개선 효과를 확인할 수 있었다.