• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.697-702
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• 2009

Filtered-x LMS algorithm maybe the most popular control algorithm used in DSP implementations of active noise and vibration control system. The algorithm converges on a timescale comparable to the response time of the system to be controlled, and is found to be very robust. If the pure tone reference signal is synchronously sampled, it is found that the behavior of the adaptive system can be completely described by a matrix of linear, time invariant, transfer functions. This is used to explain the behavior observed in simulations of a simplified single input, single output adaptive system, which retains many of the properties of the multichannel algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.3
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• pp.157-162
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• 2014

The active noise control(ANC) method for noise problems solution generally uses filtered-X LMS algorithms. However, Filtered-X LMS algorithms were mainly used but these had a limitation that had to measure a transfer function of secondary noise path. However, newly proposed correlation-LMS algorithms have slightly much calculation and are minutely behind performance, these have a advantage not in measuring transfer function onerously so that we can easily adapt these in real time. Thus Co-LMS algorithm was developed to improve the real-time implementation performance under the variable input noise such as road noise environment. In this paper, the performance of the Co-LMS is presented in comparison with that of the Filtered-X LMS algorithm. Simulation results show that active noise control using Co-LMS have slightly much calculation and are minutely behind performance, these have a advantage not in measuring transfer function onerously so that we can easily adapt these in real time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1528-1535
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• 1994

In this paper, a filtered-X LMS algorithm by new error path identification method is proposed for active noise control system. The proposed algorithm identifies accurately the error path transfer function using three microphones and the control of error signal through double loop scheme with on-line. In the computer simulation using the sinusoidal and the practical duct noise, the proposed algorithm reduces noise level about 29.1dB and 10.4dB, respectively. We can observe the improvement of about 0.5dB and 2.5dB in noise level compared with that obtained using the filtered-X LMS algorithm of Eriksson model.

• Journal of KSNVE
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• v.8 no.3
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• pp.485-493
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• 1998

Many of the adaptive noise control systems utilize a form of the least mean square (LMS) algorithms. In the active control of noise, it is common practice to locate an error microphone far from the control source to avoid the near-field effects by evanescent waves. Such a distance between the control source and the error microphone makes a certain level of time-delay inevitable and, hence, may yield undesirable effects on the convergence properties of control algorithms such as filtered-x LMS. This paper discusses the dependence of the convergence rate on the acoustic error path in these popularalgorithms and introduces new algorithms which increase the convergence region regardless of the time-delay in the acoustic error path. Performances of the new LMS algorithms are presented in comparison with those by the conventional algorithms based on computer simulations and experiments.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.4
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• pp.239-246
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• 2003

Application of the filtered-x Least Mean Square(LMS) adaptive filter to active noise control requires to estimate the transfer characteristics between the output and the error signal of the adaptive controller. In this paper, we derive the filtered-x adaptive noise control algorithm and analyze its convergence behavior when the acoustic noise consists of multiple sinusoids. The results of the convergence analysis of the filtered-x LMS algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Simulation results are presented to support the theoretical convergence analysis.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2
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• pp.40-49
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• 1995

Application of the filtered-x LMS adaptive filter to active noise cancellation requires to estimate the transfer charactersitics between the output and the error signal of the adaptive canceler. In this paper, we derive the filtered-x adaptive noise cancellation algorithm and analyze its convergence behavior when the acoustic noise consists of multiple sinusoids. The results of the convergence analysis of the filtered-x LMS algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to strongly affected by the accuracy of the phase response estimate. Simulation results are presented to support the theoretical convergence analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.447-450
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• 2003

This paper concerns on application of active magnetic bearing(AMB) system to levitate the elevation axis of an electro-optical sight mounted on moving vehicles. In such a system. it is desirable to retain the elevation axis within the predetermined air-gap while the vehicle is moving. A disturbance compensation control is proposed to reduce the base motion response. In the consideration of the uncertainty of the system model, a filtered-x least-mean-square(FXLMS) algorithm is used to estimate adaptively the frequency response function of the feedforward control which cancels disturbance responses. The frequency response function is fitted to an optimal feedforward control. Experimental results demonstrate that the proposed control reduces the air-gap deviation to 27.7% that by feedback control alone.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.130-135
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• 2006

There have been experiments dealing with the possibility of the actualization of the ANC system by means of operating the DSP adaptation filter. This filter is composed of various filters(including X-LMS algorithm, Filter-U algorithm, and Full-Feedback-Filter-U algorithm) that use ventilation fans and loudspeakers as a primary source in a circular duct as an experimental device. In this operation, the ANC system using the X - LMS algorithm was found to be more effective in reducing noise than without such system. When applying the input signal of the DSP board Full Feedback-Filtered-U algorithm system while having in mind that the additionally installed second control signal was gone through feedback and mixed into the detection microphone installed near the ventilation fan when using the first ventilation fan, the system was not emitted, but maintained stable during the operation of the control filter. At this point, noise tended to decrease at a maximum of l0dB compared to other algorithms at the frequency band of 170-250Hz.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.280-287
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• 2016

In this paper, we propose a normalization algorithm that can be applied to adaptive filters for multi-channel active noise control. The FxLMS (Filtered-x Least Mean Square) algorithm for the single-channel active noise control can be normalized in the same way as the NLMS (Normalized Least Mean Square) algorithm, whereas in case of the multi-channel active noise control, the single-channel normalization for the FxLMS algorithm cannot be extended to the normalization for the multi-channel FxLMS algorithm straightforwardly. First, we adopt a generalized normalization algorithm for the multi-channel FxLMS algorithm based on the principle of minimal disturbance and then, proposed a normalized algorithm considering only diagonal elements to avoid computation for matrix inversion. We carried out performance comparisons of the proposed algorithm with other algorithms without normalization. It is shown that the proposed algorithm presents better convergence characteristics under non-stationary environments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.402-407
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• 1994

유연한 구조물의 진동문제에 대해 Filtered-X LMS 알고리즘을 이용한 제어계를 구성하고 디지탈 신호처리보드를 이용하여 실시간 제어를 수행하였다. 엑추에이터는 피에조 세라믹을 사용하였고 정현파 및 잡색잡음 가진 형태의 외란을 가하였다. 실험결과 1차 고유주파수에서 7dB 이상의 진동저감을 할 수 있었으며 관심 주파수영역 내에서 진동이 고르게 저감되었다.