• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.2
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• pp.281-287
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• 1997

In the conventional inverse modeling method for on-line modeling of the secondary path transfer function, the signal to noise ratio between the arbitrary random signal and the plant noise have to keep at -10 - -20 dB. For these reasons, the modeling can't be exactly implemented by the conventional method alone and the convergence time for modeling becomes too long. In this study, by combining the conventional inverse modeling method with an adaptive line enhancer, or with an adaptive noise canceller, a rigorous transfer functions of secondary path modeling and the control of a primary noise have been implemented simultaneously.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.283-287
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• 1996

The exhaust noise reduction of automobile with the active muffler is experimentally investigated. The control algorithm is the filtered-x LMS algorithm and the inverse algorithm with the adaptive line enhancer. Also, the control efficiency is increased with synthesized second harmonic engine frequency. In the experiment, the active muffler is applied to the end of exhaust system in automobile and the control with on-line secondary path modeling method(inverse algorithm) is compared the control of off-line secondary path modeling method. As secondary path transfer functions are changed, the experimental results show that the control performance with on-line method is more efficient than that with off-line method in the exhaust noise reduction of automobile.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.197-205
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• 2014

In applications of adaptive noise control or active noise control, the presence of a transfer function in the secondary path following the adaptive controller and the error path, been shown to generally degrade the performance of the Least Mean Square (LMS) algorithm. Thus, the convergence rate is lowered, the residual power is increased, and the algorithm can become unstable. In general, in order to solve these problems, the filtered-x LMS (FX-LMS) type algorithms can be used. But these algorithms have slow convergence speed and weakness in the environment that the secondary path and error path are varied. Therefore, I present the new algorithm called the "Bi-directional Filtered-x (BFX) LMS" algorithm with nearly equal computation complexity. Through experimental study, the proposed BFX-LMS algorithm has better convergence speed and better performance than the conventional FX-LMS algorithm, especially when the secondary path or error path is varied and the impulsive disturbance is flow in.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.251-252
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.39-40
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.35-36
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• 2007

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1992.11a
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• pp.56-59
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• 1992

Adaptive active attenuation of noise in a duct is considered. A duct is modelled when the acoustic feedback exists. The secondary path transfer function is estimated using multiple model approaches. An IIR structure is assumed for the control filter, and the recursive least mean squares algorithm is used to adjust the filter coefficients.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.299-301
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• 1992

The adaptive active noise control algorithm for duct noise attenuation is considered. A new algorithm to estimate the secondary path transfer function using multiple models is presented. The computational burden of the proposed algorithm is much smaller than the existing methods, so it could be applied to the multi-channel cases. Computer simulations were done to show the effectiveness of the proposed algorithm in a duct case.

• Journal of KSNVE
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• v.10 no.6
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• pp.941-948
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• 2000

Active noise control is an approach to reduce the noise by utilizing a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and an adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Oppenheim assumed that transfer function characteristics from the canceling source to the error sensor is only a propagation delay. This paper proposes a modified Oppenheim algorithm by considering transfer characteristics of speaker-path-sensor This transfer characteristics is adaptively cancelled by the proposed adaptive modeling technique. Feasibility of the proposed method is proved by computer simulations with artificially generated random noises and sine wave noise. The details of the proposed architecture. and theoretical simulation of the noise cancellation system for three dimension enclosure are presented in the Paper.