• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.343-348
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• 2011

This paper introduces a design for real time wireless headset using ANC (active noise control) system based on NFxLMS adaptive filter algorithm. The training time of the proposed system is significantly reduced by using the RMS delay spread of a channel as an error correction parameter, and convergence rate of the FxLMS filter has been improved with updating the coefficients of the NFxLMS filter, which we have got during the training process. Our system has shorter training time and better convergence rate at the same noise reduction level than the conventional system under real noisy environment.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1131-1138
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• 2003

Active noise control(ANC) is an approach to noise reduction in which a secondary noise source destructively interferes with the unwanted noise is introduced. Generally, the performance of ANC is determined how well a secondary noise tracks noises. A secondary noise is generated from the cancelling speaker and a error sensor pick up error signal. The transfer function between the cancelling speaker and the error sensor is not flat and distorts secondary noises. Consequently, the performance of ANC is degraded by the transfer function. In this paper, a single sensor ANC which considers the characteristics of the speaker and the error sensor is proposed. To reduce distortion of secondary noises, the transfer function is estimated by adaptive inverse modelling and the primary noises are estimated by Kalman filter. Experimental results show that the proposed single sensor ANC effectively attenuates noises.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.622-627
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• 2008

Experiment of active noise control on supersonic jet noise was conducted by use of microjet injection. The microjets were injected to the shear layer of the main jet through 22 small holes at the lip of a rectangular nozzle. Based on the measurement of farfield sound pressure, it was found that the jet noise was effectively reduced by several dB(in some cases up to 10 dB). The power levels of all measurement points were also reduced by use of microjet injection. The microjet affected not only the broadband noise but also the screech tone noise. The sound pressure level, the frequency of the screech tone, and the structure of the jet could be changed by the microjet. Flow visualization with schlieren technique was also made to observe the effect of microjet on the flow field.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.47-55
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• 2003

This paper Presents active control algorithm using probability density function of structural energy. It is assumed that the structural energy under excitation has Rayleigh probability distribution. This assumption is based on the fact that Rayleigh distribution satisfies the condition that the structural energy is always positive and the occurrence probability of minimum energy is zero. The magnitude of control force is determined by the probability that the structural energy exceeds the specified target critical energy, and the sign of control force is determined by Lyapunov controller design method. Proposed control algorithm shows much reduction of peak responses under seismic excitation compared to LQR controller, and it can consider control force limit in the controller design. Also, chattering problem which sometimes occurs in Lyapunov controller can be avoided.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.625-629
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• 2014

In this paper, a tile projector for the active control of low-frequency underwater echoes is studied using finite element method. Compared to the existing underwater actuators used for echo reduction, the tile projector is better suited for covering a wide area such as the hull of a submarine. In order to actively match the acoustic impedance at the water-object interface, the projector is driven to radiate a pressure wave that is the inverted replica of the echo at the interface. Finite element simulations demonstrate significant echo reductions due to the active impedance matching by the tile projector.

• Smart Structures and Systems
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• v.20 no.3
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• pp.273-283
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• 2017

This paper presents and compares three feedback control strategies for active control of noise inside a 3-D vibro-acoustic cavity. These are a) control strategy based on direct output feedback (DOFB) b) control strategy based on linear quadratic regulator (LQR) to reduce structural vibrations and c) LQR control strategy with a weighting scheme based on structural-acoustic coupling coefficients. The first two strategies are indirect control strategies in which noise reduction is achieved through active vibration control (AVC), termed as AVC-DOFB and AVC-LQR respectively. The third direct strategy is based on active structural-acoustic control (ASAC). This strategy is an LQR based optimal control strategy in which the coupling between the various structural and the acoustic modes is used to design the controller. The strategy is termed as ASAC-LQR. A numerical model of a 3-D rectangular box cavity with a flexible plate (glued with piezoelectric patches) and with other five surfaces treated rigid is developed using finite element (FE) method. A single pair of collocated piezoelectric patches is used for sensing the vibrations and applying control forces on the structure. A comparison of frequency response function (FRF) of structural nodal acceleration, acoustic nodal pressure, and piezoelectric actuation voltage is carried out. It is found that the AVC-DOFB control strategy gives equal importance to all the modes. The AVC-LQR control strategy tries to consume the control effort to damp all the structural modes. It is seen that the ASAC-LQR control strategy utilizes the control effort more intelligently by adding higher damping to those structural modes that matter more for reducing the interior noise.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.692-694
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• 1993

Acoustic noise from the various facilities makes man unpleasant and let researchers find the way for reducing it on environmental point of view. Special way to reduce the acoustic noise had suggested by the concept of Active Silencer. But, it has propagation delay time accumulated during the signal passage and howling effect. This paper suggestes a way to anhilate howling effects, and reduces the total delay time drasticaly by attaching microphone to the speaker. This paper will show how it works by some materials.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1203-1206
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• 2021

소음은 난청, 스트레스 등의 원인이 된다. 본 연구에서는 ANC(Active Noise Cancellation)을 바탕으로, 기술적인 방법을 통해 소음을 저감 시키는 스피커를 구현하였다. ANC 란 소음 주파수의 위상을 180° 변환하여 주파수와 레벨이 동일한 역 소음을 발생시켜 주변 소음을 저감, 차단하는 기술이다. 현재 시중 제품들에 적용되는 일반적인 ANC 의 경우, 피드백(Feedback) 방식이라는 점과 시간 지연(Time gap)이 발생한다는 한계가 있다. 이를 보완하기 위해 AI 학습으로 소음을 미리 예측하여 시간 지연을 줄이는 방법을 고안했다. 순환 신경망(RNN)의 장기의존성 문제를 해결하는 시계열 예측 딥러닝 알고리즘인 LSTM(Long Short-Term Memory Network) 모델을 사용하였다. 또한, AI 학습 효율을 향상시킬 수 있는 하드웨어 장비들을 활용하였다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.1
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• pp.94-99
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• 1997

There are several factors that have influence on the phase noise of an oscillator. But one of the major factors is the flicker noise of a transistor, since the phase noise of an oscillator is generated by mixing the carrier with the low frequency noise near the DC having the characteristic of 1/f. In this paper, we have presented a method on reducing the phase noise of an oscillator by using a low-frequency feedback circuit based on an active bias circuit, and have fabricated a DRO for a DBS receiver. Measurement results show that the phase noise is -92 dBc/Hz at the 10 KHz offset frequency, and from these results we have found out that the reduction method is very effective.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1220-1225
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• 2010

This paper proposes a novel active noise control (ANC) approach that uses an IIR filter and neural network techniques to effectively reduce interior noise. We construct a multiple-channel IIR filter module which is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimization based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Lastly, we present the results of a numerical study to test our ANC methodology with realistic interior noise measurement obtained from Korean railway trains.