• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.5
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• pp.545-557
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• 2021

Engine is the main source of vibration that generates unwanted noise and vibration of vehicle chassis. Especially, in submarine applications, radiation of noise signatures can be detected at some distance away from the submarine using a sonar array. Thus quiet operation is crucial for submarine's survivability. This study addresses reduction of the force transmissibility originating from engines and transmitted to hull through engine mounts. An inertial damper, as an actuator of hybrid mount system, is addressed to reduce even further the level of vibration. Narrow band FxLMS algorithms are broadly used to cancel the vibration of engine mount because of its excellent performance of canceling narrow band noise. However, in real active dampers, the maximum displacement of damper mass is kinematically restricted. When the control input signal from the FxLMS algorithm exceeds this limitation, the damper mass will collide with the mechanical stops and results in many problems. Originated from these, a modified narrow band FxLMS algorithm based on the equalizer technique with the maximum allowable displacement of active damper mass is proposed in this study. Some simulation results showed that the propose algorithm is effective to suppress vibration of engine mount while ensuring given displacement constraint.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.95-98
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• 2013

The LMS(Least Mean Square) algorithm, one of the most famous, is generally used because of tenacity and high mating spots and simplicity of realization, But it has trade-off between nonuniform collection and EMSE(Excess mean square error). To overcome this weakness, a variable step size is used widely, but it needs a lot of calculation loads. In this paper, we suggest changed algorithm in case of environment changes of cars and reduce amount of calculation as it uses original signal and noise signal of IGC(Instantaneous Gain Control) algorithm. In this paper, logarithmic function is removed because of real-time processing IGC. The performance of proposed algorithm is tested to adaptive noise canceller in automobile.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.1016-1019
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• 2004

The study of the noise reduction of an automobile has been concentrated on the reduction of the automotive engine noise because the engine noise is the major cause of automotive noise. However, many studies of automotive engine noise led to the interest of the noise reduction of the exhaust and intake system. The method of the reduction of the induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to this problem, the modified FXLMS algorithm using Moving Bandpass Filter was proposed. In this study, MBPF was implemented and use ANC for automotive intake under revived rapidly accelerated driving conditions and it was verified its performance.

• Journal of information and communication convergence engineering
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• v.2 no.2
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• pp.89-92
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• 2004

An adaptive algorithm for reducing the hardware complexity is presented. This paper proposes a modified LMS algorithm for the adaptive system and analyzes its convergence characteristics mathematically. An objective of the proposed algorithm is to reduce the hardware complexity. In order to test the performances, it is applied to the echo canceller, and a program is described. The results from simulations show that the echo canceller adopting the proposed algorithm achieves almost the same performances as one adopting the NLMS algorithm. If an echo canceller is implemented with this algorithm, its computation quantities are reduced to the one third as many as the one that is implemented with the NLMS algorithm, without so much degradation of performances.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1917-1919
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• 2002

An adaptive algorithm for the acoustic echo canceller is presented. This paper proposes a modified LMS algorithm for the adaptive filter and applys the algorithm to he acoustic echo canceller, An objective of the proposed algorithm is to reduce the hardware complexity. In order to est the performances, a model of the echo path is established, and a program is described. The impulse reponses of the echo path have the length of 125msec or ore, and then the FIR filter with 1000 taps is required. he results from simulations show that the acoustic echo canceller adopting the proposed algorithm achieves the ERLE of 25dB or more within 1sec. If an echo canceller is implemented with this algorithm, its computation quantity s reduced to two times less than the one that is implemented with the normal LMS algorithm, without the degradation of performances.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.9-22
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• 2019

In this paper, we propose a method that can be applied to the efficient implementation of multi-channel active noise controller. Since the normalized MFxLMS (Modified Filtered-x Least Mean Square) algorithm for the multi-channel active noise control requires a large amount of computation, the difficulty has lied in implementing the algorithm using a low-cost MCU (Microcontoller Unit). We implement the multi-channel active noise controller efficiently by optimizing the software based on the features of the MCU. By maximizing the usage of single-cycle MAC (Multiply- Accumulate) operations and minimizing move operations of the delay memory, we can achieve more than 3 times the performance in the aspect of computational optimization, and by parellel processing using the auxillary processor included in the MCU, we can also obtain more than 4 times the performance. In addition, the usage of additional parts can be minimized by maximizing the usage of the peripherals embedded in the MCU.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.201-201
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• 2004

• The Journal of the Acoustical Society of Korea
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• v.15 no.1E
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• pp.89-94
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• 1996

This paper deals with the application of the LMS algorithm as a decision-directed adaptive equalizer in a communication receiver which also employs a sophisticated decoding scheme such as the Viterbi algorithm, in which the desired signal, hence the error, is not available until several symbol intervals later because of decoding delay. In such applications the implemented weight updating algorithm becomes DLMS and major penalty is reduced convergence speed. Therefore, every effort should by made to keep the delay as small as possible if it is not avoidable. In this paper we present a modified implementation in which the effects of the decoding delay can be avioded and perform some computer simulations to check the validity and the performance of the new implementation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.163-166
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• 2010

본 논문에서는 현재 상용화 되어있는 WCDMA용 ICS (Interference Cancellation System) 중계기의 성능 개선을 위한 개선된 LMS 알고리즘을 연구하였다. ICS 중계기의 수신으로 입력되는 신호는 수신 신호와 궤환되어 입력되는 신호로 구성된다. 이렇게 입력되는 궤환 신호를 LMS와 같은 적응형 채널 추정 알고리즘을 통해 제거하는 기술이 ICS 중계기의 핵심 요소이다. 중계기의 저비용 및 단순화를 위해서는 기존에 사용되어온 적응형 채널 추정 알고리즘의 단순화가 필요하다. 실험을 통해 기존 NLMS 알고리즘 및 계산 복잡도 감소를 위해 수정된 LMS 알고리즘을 MSE (Mean Square Error) 기준에서 성능 비교를 하였다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1987.11a
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• pp.79-81
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• 1987

In this paper we propose a fast adaptive least squares algorithm for linear phase FIR filters. The algorithm requires 10m multiplications per data point where m is the filter order. Both linear phase cases with constant phase delay and constant group delay are examined. Simulation results demonstrate that the proeposed algorithm is superior to the LMS gradient algorithm and the averaging scheme used for the modified fast Kalman algorithm.