• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.179-182
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• 1998

본 논문에서는 보청기의 다채널 구조를 이용하여 음향 궤환 제거의 대역폭과 대역의 위치를 조절할 수 있는 새로운 알고리듬을 제안하였다. 제안한 알고리듬에서는 음향 궤환 제거기가 보청 알고리듬의 각 주사수 대역별로 따로 연결되어 있기 때문에 주파수 대역과의 연결에 따라 특정 주파수 대역에서만 음향 궤환이 이루어지게 할 수도 있고, 기존의 음향 궤환 제거 방식과 같이 전 주파수 대역에서도 음향 궤환 제거를 할 수 있으므로 보다 효과적이고 유연한 알고리듬이라 할 수 있다. 따라서 성능면에서도 기존의 알고리듬과 같거나 특별한 조건하에서는 더 나은 성능을 보인다. 제안한 알고리듬에 대해 3개의 채널을 가지는 보청기 구조와 8개의 채널을 가지는 보청기 구조에서 실험을 행하였다. 음향 궤환 경로는 문헌의 자료를 참고하여 2가지를 만들어 이들 음향 궤환 경로의 특성이 집중되어 있는 대역으로 제한하여 음향궤환 제거를 한 결과 전주파수 대역에서 음향 궤환 제거를 한 경우보다 이들 제한된 대역내에서는 더 음향 궤환이 잘 이루어졌다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.887-892
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• 2008

This paper is on a new adaptive algorithm which can cancel the acoustic feedback signals in the digital hearing aids. The proposed algorithm uses the normalized LMS algorithm with decorrelators. By doing so, it can be reduced the autocorrelation for the voice signals. To analyze the convergence characteristics of the proposed algorithm, the simulations were carried out about various input signals. And we had compared the performances of convergence for this algorithm with the ones for the NLMS algorithm. As the results of simulations, it is proved that the feedback canceller adopting this algorithm shows about 5-10 dB more high SNR than the NLMS algorithm for the colored inputs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.911-916
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• 2010

This paper proposes a new algorithm to cancel the acoustic feedback and noise signals in digital hearing aids. The proposed algorithm combines the feedback canceller to remove acoustic feedback signals and the noise canceller to reduce background noises. The feedback canceller is implemented by normal adaptive FIR filter, and the noise canceller is implemented by using the Wiener solution in frequency domain. This noise canceller has the transfer function presented by the power spectral density of signals. To verify the performances of the proposed algorithm, the simulations were carried out for the system. As the results of simulations, it was proved that we can advance 10.85dB output SNR on the average for the forward path gain of 0dB, and 11.04dB output SNR on the average for the forward path gain of 6dB, in the case of using the proposed algorithm.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4
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• pp.38-46
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• 1999

In this paper, two methods were proposed to improve the performance of adaptive feedback cancellation in hearing aids. One is “Orthogonality principle acoustic feedback cancellation method(Orthogonality principle method)” to track optimal solution with monitoring the instantaneous gradient, the other is a method using the CLMS algorithm(CLMS method). In many simulation conditions, adaptive feedback cancellation method proposed in this paper was much better than Greenberg method by Sum-method LMS algorithm which is known the most excellent method by now in case of system mismatch, SNR and segmental SMR. Also. Orthogonality principle method is as good as CLMS method in terms of adaptive feedback cancellation in many simulation conditions.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1249-1256
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• 2019

In this paper, we propose a new algorithm to remove acoustic feedback and noise in hearing aids. Instead of using the conventional FIR structure, this algorithm is a deep learning algorithm using neural network adaptive prediction filter to improve the feedback and noise reduction performance. The feedback canceller first removes the feedback signal from the microphone signal and then removes the noise using the Wiener filter technique. Noise elimination is to estimate the speech from the speech signal containing noise using the linear prediction model according to the periodicity of the speech signal. In order to ensure stable convergence of two adaptive systems in a loop, coefficient updates of the feedback canceller and noise canceller are separated and converged using the residual error signal generated after the cancellation. In order to verify the performance of the feedback and noise canceller proposed in this study, a simulation program was written and simulated. Experimental results show that the proposed deep learning algorithm improves the signal to feedback ratio(: SFR) of about 10 dB in the feedback canceller and the signal to noise ratio enhancement(: SNRE) of about 3 dB in the noise canceller than the conventional FIR structure.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.102-110
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• 2017

In this paper, we have implemented an real-time adaptive feedback cancellation(AFC) algorithm that can be applied to multi-channel digital hearing aid. Multichannel digital hearing aid typically use the FFT filterbank based Wide Dynamic Range Compression(WDRC) algorithm to compensate for hearing loss. The implemented real-time acoustic feedback cancellation algorithm has one integrated structure using the same FFT filter bank with WDRC, which can be beneficial in terms of computation affecting the hearing aid battery life. In addition, when the AFC fails to operate due to nonlinear input and output, the reduction gain is applied to improve robustness in practical environment. The implemented algorithm can be further improved by adding various signal processing algorithm such as speech enhancement.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.229-232
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• 2001

콘형 스피커를 사용한 임피던스 흡음 제어시스템에서는 진동판의 진동속도와 음압 모두를 궤환하는데 이는 궤환 이득이 큰 반면에 궤환 루프상의 요소들 때문에 안정한 동작이 곤란하였다. 이 연구에서는 전기단 접속형 제어시스템과 속도 궤환형 제어시스템의 적용에 대해 그 가능성을 확인하였다.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.1-10
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• 2012

The linear and decision-feedback equalization can mitigate time-varying intersymbol interference (ISI) caused by time-varying multipath propagation for underwater acoustic channels. The perfect elimination of interference components, however, is difficult using the linear equalization and the decision feedback equalizer has an error propagation problem. To overcome these shortcomings, this paper proposes an equalizer mode selection method using training sequences. The proposed method selects an equalization mode corresponding to the signal-to-noise ratio (SNR). If the SNR is low, the proposed system operates the linear equalizer for preventing the error propagation and if the SNR is high, the decision feedback equalizer for eliminating the residual ISI. Therefore, the proposed method can improve the error performance compared to the conventional equalizers. The computer simulation shows the proposed method improves the bit error performance using practical underwater channels responses acquired from the sea experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7C
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• pp.413-420
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• 2011

This paper proposes a new adaptive algorithm to cancel the acoustic feedback and noise signals in the binaural hearing aids. The convergence performances of the proposed algorithm are improved by updating coefficients of the feedback canceller after the speech signal is cancelled from the residual signal with dual microphones. The feedback canceller firstly cancels the feedback signal from the microphone signal, and then the noise canceller reduces the noise by the beamforming method. To assure that binaural hearing aids converge stably, the left-sided hearing aid only is converged firstly, next the right-sided hearing aid only is converged. To verify performances of the proposed algorithm, simulations were carried out for a speech. As the results of simulations, it was proved that we can advance 14.43dB SFR(Signal to Feedback Ratio) on the average for the feedback canceller, 10.19dB SNR(Signal to Noise Ratio) improvement on the average for the noise canceller, in case that this algorithm is used.