• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.471-473
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• 1998

본 논문에서는 뉴로-퍼지 제어기를 이용한 능동 소음제어기를 구현하였다. 능동 소음제어기는 잡음에 의하여 왜곡된 신호로부터 잡음을 제거하여 원 신호를 복원하는 제어시스템이다. 일반적으로 잡음의 특성이 시간에 따라 변화하고, 전달특성이 비선형적이므로 고정된 제어기에 의해서는 제어할 수 없다. 이 논문에서는 뉴로-퍼지 제어기를 사용하였고, 파라미터를 오차 역전과 학습을 통하여 변화시킴으로써 잡음의 특성에 효과적으로 적응하는 능동 소음제어기를 구성하였다. 시뮬레이션을 통하여 여러 종류의 신호에 대해서 랜덤 노이즈를 발생시키고 구성된 제어기의 성능을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.22.1-22
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• 2001

In this paper we present Multiple-Channel Active Noise Control[ANC] system by employing Independent Component Analysis[ICA] and Adaptive Network Fuzzy Inference System[ANFIS]. ICA is widely used in signal processing and communication and it use prewhiting and appropriate choice of non-linearities, ICA can separate mixed signal. ANFIS controller is trained with the hybrid learning algorithm to optimize its parameters for adaptively canceling noise. This new method which minimizes a statistical dependency of mutual information(MI) in mixed low frequency noise signal and there is no need to secondary path modeling. The proposed implementations achieve more powerful and stable noise reduction than Filtered-X LMS algorithms which is needed for LTI assumption and precise secondary error

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.96-102
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• 2010

This paper proposes a new adaptive algorithm to cancel the acoustic feedback and noise signals in the digital hearing aids. The proposed algorithm improves its convergence performances by canceling the speech signal from the residual signal using two microphones. The feedback canceller firstly cancels the feedback signal among the mic signal, and then it is reduced the noise using the beamforming method. To verify the performances of the proposed algorithm, the simulations were carried out for some cases. As the results of simulations, it was proved that the feedback canceller and the noise canceller advance about 14.43 dB for SFR, 10.19 dB for SNR respectively during speech, in the case of using the new algorithm.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.76-80
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• 2001

Unsteady compressible Euler equation is solved and the high-order, high-resolution numerical solver, physical boundary condition, adaptive nonlinear artificial dissipation model and conformal mapping are applied to computation of steady transonic flow and unsteady acoustics. The acoustic characteristics of axi-symmetric duct and two dimensional straight/S channel are studied and the computation results shows good agreements with linear analysis. In transonic case, local time stepping and canceling-the-residual techniques are used for convergence acceleration. The aspect of flow and acoustics in S-channel and the Pattern of noise radiation is changed by inflow Mach no. and static pressure at fan-face.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.559-567
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• 2020

This paper proposes a noise cancelling algorithm to remove own-ship noise for a towed array sonar. Extra beamforming is performed using partial channels of the acoustic array to get a reference beam signal robust to the noise bearing. Frequency domain Adaptive Noise Cancelling (ANC) is applied based on Normalized Least Mean Square (NLMS) algorithm using the reference beam. The bearing of own-ship noise is estimated from the coherence between the reference beam and input beam signals. Own-ship noise level is calculated using a beampattern of the noise with estimated steering angle, which prevents loss of a target signal by determining whether to update a filter so that removed signal level does not exceed the estimated noise level. Simulation results show the proposed algorithm maintains its performance when the own-ship gets out off its bearing 40 % more than the conventional algorithm's limit and detects the target even when the frequency of the target signal is same with the frequency of the own-ship signal.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.34 no.5
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• pp.377-384
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• 2015

An active noise control (ANC) algorithm for noise canceling headphone is proposed. In this study, the feedback ANC operated with the filtered-x least mean square algorithm (FxLMS) algorithm is used to attenuate the undesired noise. Also an adaptive residual music canceller (RMC) is proposed for enhancing the accuracy of the reference signal of the feedback ANC. Simulation results show that a high quality of music sound can be consistently achieved in a time-varying secondary path situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1713-1719
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• 2022

As the noise canceler with a small processing delay increases the sampling frequency, a better-quality output can be obtained. For a single buffer, processing delay occurs because it is impossible to write new data while the processor is processing the data. When synthesizing with anti-noise and output signal, this processing delay creates additional buffering overhead to match the phase. In this paper, we propose an accelerator structure that minimizes processing delay and increases processing speed by alternately performing read and write operations using the Symmetric Even-Odd-buffer. In addition, we compare the structural differences between the two methods of noise cancellation (Fast Fourier Transform noise cancellation and adaptive Least Mean Square algorithm). As a result, using an Symmetric Even-Odd-buffer the processing delay was reduced by 29.2% compared to a single buffer. The proposed Symmetric Even-Odd-buffer structure has the advantage that it can be applied to various canceling algorithms.

• Journal of IKEEE
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• v.22 no.4
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• pp.1109-1114
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• 2018

Electroencephalogram (EEG) is a tool used to study brain activity caused by external stimuli. In this process, artifacts are mixed and it is easy to distort the signal, so post-processing is necessary to remove it. Independent Component Analysis (ICA) is a widely used method for removing artifact. This method has a disadvantage in that it has excellent performance but some loss of brain wave information. In this paper, we propose a method to reduce EEG information loss by restricting the filter coverage using eye blink information obtained from Eyetracker. We then compared the results of the proposed method with the conventional method using quantization methods such as Signal to Noise Ratio (SNR) and Spectral Coherence (SC).

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.111-114
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• 2001

In this paper, we supposed teller following algorithm that using sound localization for developing dialog type humanoid robot. A sound localization is studied for develop the techniques of an efficient 3-D sound system based on the psychoacoustics of spatial hearing with multimedia or virtual reality. When a robot talk with human, it is necessary that robot follow human for improved human interface and adaptive noise canceling. We apply this algorithm to robot system.