• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.231-238
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• 2004

This paper presents the high speed noise reduction processing system using the modified discrete fourier transform(MDFT) on the frequency domain. The proposed filter uses the linear prediction coefficients of the adaptive line enhance(ALE) method based on the Sign algorithm The signals with a random noise tracking performance are examined through computer simulations. It is confirmed that the fast adaptive digital filter is realized by the high speed adaptive noise reduction(HANR) algorithm with rapid convergence on the frequency domain(FD).

• Journal of IKEEE
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• v.24 no.2
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• pp.570-578
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• 2020

In this paper, we propose an efficient method for implementing the adaptive second-order Volterra filter. To reduce computational load, the UCFD-SVF has been proposed. The UCFD-SVF, however, shows deteriorated convergence performance. We propose a new method that initializes the adaptive filter weights periodically on the fact that the energy of the filter weights is slowly increased. Furthermore, we propose another method that the interval for the weight initialization is variable to guarantee the performance and we shows the method gives the better performance under the non-stationary environment through the computer simulation for the adaptive system identification.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.3-15
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• 2000

In this paper we present a new image denoising filter that can suppress additive noise components while preserving signal components in the wavelet domain. The proposed filter, which we call an adaptive wavelet shrinkage(AWS) filter, is composed of two operators: the wavelet killing operator and the adaptive shrinkage operator. Each operator is selected based on the threshold value which is estimated adaptively by using the local statistics of the wavelet coefficients. In the wavelet killing operation, the small wavelet coefficients below the threshold value are replaced by zero to suppress noise components in the wavelet domain. The adaptive shrinkage operator attenuates noise components from the wavelet components above the threshold value adaptively. The experimental results show that the proposed filter is more effective than the other methods in preserving signal components while suppressing noise.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.53-59
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• 1989

A new proposed method can separate heart sounds and lung sounds by the realization of adaptive noise canceler using adaptive lattice Wiener filter in contrast to adaptive transversal LMS filter and high pass filter as before. Lung sounds and ECG signal are detected for this purpose, and especially the second heart sounds are reduced by finding T wave location with a T wave seeking algorithm. As a result, for heart sounds reduction It was found that adaptive transversal LMS filter required 100-200's orders, 75-100's orders In adaptive transversal MLMS filter, and only 10-20's orders in adaptive lattice Wiener filter. Adaptive filtering technique has shown greater accuracy than high pass filtering without loss of low frequency component.

• The Journal of the Acoustical Society of Korea
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• v.32 no.6
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• pp.518-524
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• 2013

In this paper, we propose a variable step size algorithm to enhance the normalized subband adaptive filter which has been proposed to improve the convergence characteristics of the conventional full band adaptive filter. The well-known Kwong's variable step size algorithm is simple, but shows better performance than that of the fixed step size algorithm. However, in case that large additive noise is present, the performance of Kwong's algorithm is getting deteriorated in proportion to the amount of the additive noise. We devised a variable step size algorithm which does not depend on the amount of additive noise by exploiting a normalized adaptation error which is the error subtracted and normalized by the estimated additive noise. We carried out a performance comparison of the proposed algorithm with other algorithms using a system identification model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.986-991
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• 2014

The PPG signal used in mobile-healthcare and telemedicine system is including the various motion artifact that is signal generated from patient's movements. Recently, although the various methods to remove motion artifacts have been suggested, the performances of these methods are still not satisfactory. Therefore, this s study suggested the novel method based on the Kalman filter and adaptive filter to remove motion artifacts, and we used various motion artifacts to analyze the performance of the proposed method. In the results of experiments, the signal-to-noise ratio of proposed method showed good performace that was 4.8 times of moving average filter.

• Proceedings of the Acoustical Society of Korea Conference
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• 1991.06a
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• pp.157-162
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• 1991

본 연구에서는 적응 whitening 필터를 이용하여 최적 레이다 신호처리기를 구현하였다. 사용된 필터는 Gram-Schmidt와 lattice 구조를 가지며, 이들을 이용하여 레이다 clutter를 제거하고, 프로세서 특성을 원하는 표적신호에 일치시킨다. 또한 필터 계수들을 변화하는 레이다 환경에 따라 조정하기 위하여 여러 가지 적응 알고리듬을 적용하였다. 실험결과 구현된 시스템은 빠른 수렴 특성을 갖고 있으며, 역행렬 연산이 필요없기 때문에 향상 안정된 특성을 보임을 알 수 있다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.189-192
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• 1998

전화망을 이용한 음성인식 시스팀에서 출력신호의 반향에 의한 입력신호의 음질 열화현상을 막기위해서 적응디지털 필터를 이용한 반향제거기가 필수적이다. 대표적인 적응 필터 알고리즘인 LMS와 NLMS 들을 각각 이용한 적응 반향제거기들과 입/출력신호의 상관계수를 이용한 개선된 적응 필터 알고리즘의 성능을 비교하였다. 개선된 알고리즘의 경우 NLMS 알고리즘의 빠른 수렴특성을 가지면서도 더블톡(double talk)구간에서의 음질왜곡 현상을 LMS보다 개선시켰다.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2204-2207
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• 2003

본 논문은 LMS 적응 필터의 수렴성능의 향상을 위한 새로운 적응신호처리 기법을 제안한다. 기존의 LMS 알고리즘의 문제점으로는 수렴특성이 입력 벡터의 자기 상관행렬의 고유치 분포에 영향을 받는다는 점이다. 본 논문은 두 선행처리 기법, 즉, 직교 변환에 의한 선행처리 기법과 split filter 구조 필터링 기법을 결합하여 보다 개선된 수렴특성을 갖는 적응신호처리 기법을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.145-151
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• 2010

This paper proposes a reverse filtering system of sound field obtaining a state of sound field transmitted from two sounds, using an adaptive filter and neural network. The proposed system uses the reverse filtering method with calculating and renewing a coefficient of a filter, using least mean square. Based on training the neural network, experiments confirm that the proposed system is effective for a simple waveform with non-linear distortion, by using neural network and adaptive filtering method.