• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.443-448
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• 2022

This paper presents a subband affine projection algorithm with variable step size to improve convergence performance in adaptive filtering applications with long adaptive filters and highly correlated input signals. The proposed algorithm can obtain fast convergence speed and small steady-state error by using different step sizes for each adaptive sub-filter in the subband structure to which polyphase decomposition and noble identity are applied. The step size derived to minimize the mean square error of the adaptive filter at each update time shows better convergence performance than the existing algorithm using a variable step size. In order to confirm the convergence performance of the proposed algorithm, which is superior to the existing algorithm, computer simulations are performed for mean square deviation(MSD) for AR(1) and AR(2) colored input signals considering the system identification model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.77-84
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• 2017

Generally, a time-varying vibration signal is generated in a rotating machine system, and when there is a failure in the rotating machine, the signal contains noise. In this paper, we propose a system consisting of an adaptive predictor and a binary tree filter bank for analyzing time - varying vibration signals with noise. And the vibration signal analyzed results in this system is used for fault diagnosis of the rotating machine. The adaptive predictor of the proposed system predicts the periodic signal components, and the filter bank system decomposes the difference signal between the input signal and the predicted periodic signal into subband. Since each subband signal includes a noise signal component due to a failure, it is possible to diagnose the failure of the using rotary machine. The validity of the proposed vibration signal analysis method is shown in the simulations, where the periodic components cancelled vibrating signals are decomposed to 32 subband, and the signal characteristics related faults are analyzed.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.347-355
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• 2000

This paper presents an adaptive AEC(acoustic echo canceller) based on the wavelet transform using M-channel subband QMF filter banks. The proposed algorithm improves the performance of AEC with a realtime process by a low complexity of wavelet transform filter banks, a subband processing and a orthogonality of wavelet subband filter. Adaptive filter coefficients of each subband are updated using LMS algorithm with a low complexity and a easy realization for a realtime processing and a reduction of hardware cost. For a input signal, a white Gaussian noise and a real speech signal with a environment noises are used for a performance estimation of the proposed algorithm. As a result of computer simulation, the proposed AEC has a low asymptotic error, a low computation complexity and a robust performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.435-441
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• 2017

Detecting an inter-harmonic accurately is not easy work, because it has small magnitude, and its frequency which can be observed is not an integer multiple of fundamental frequency. In this paper, a new method using filter bank system and adaptive predictor is proposed. Filter bank system decomposes input signal to sub bands. In adaptive predictor, inter-harmonic is detected with decomposed sub band signal as input, and error signal as output. In this scheme, input-output characteristic of adaptive predictor is notch filter, as predicted harmonic is canceled in error signal, so detecting an inter-harmonic can be possible. Magnitude and frequency of detected inter-harmonic is estimated by recursive algorithm. The performances of proposed method are evaluated to sinusoidal signal model synthesized with harmonics and inter-harmonics. And validity of the method is proved as comparing the inter-harmonic detection results to MUSIC and ESPRIT.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.264-273
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• 2002

Adaptive filters cannot exactly estimate the echo path of the receiving room because of the cross-correlation of stereo signals. In this paper, a new pre-processing method reducing the cross-correlation without degradation of stereophony is proposed to enhance the performance of stereophonic acoustic echo canceller. To reduce the cross-correlation, absolutes of two orthogonal signals derived from each channel signals are added to original channel signals. Assuming that the power of each channel signal is larger than that of the cross-correlation, the computation of pre-processing can be reduced. As results of simulations, it is shown that the performance of stereo acoustic echo canceller with the proposed pre-processing method is better than that of conventional ones.

• Journal of Biomedical Engineering Research
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• v.23 no.5
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• pp.333-340
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• 2002

Powerline interference in bioelectric recordings is a common source of noise. IEF(Incremental Estimation Filter) has been used to eliminate powerline interferences in biosignals, especially in ECG(Electrocadiogram) signals. The constant incremental factor in the IEF filter, which affects the performance of noise rejection, is usually determined empirically or experimentally based on the input signals. This paper presents the design of neural network based IEF filter for time-varying control of the incremental factor. The proposed IEF filter is evaluated by applying to artificial signals as well as ECG signals of MIT-BIH database. For the relative comparison of noise-rejection performance, it is compared with adaptive noise canceler and conventional IEF filter. Simulation results show that the neural network based IEF filter outperforms these adaptive filters with respect to convergence speed and noise rejection is specific frequencies.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.8-14
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• 2001

In this paper, we present a new cost function for subband block adaptive algorithm and block conjugate gradient algorithm for noise cancellation of acoustic signal. For the cost function, we process the subband signals with data blocks for each subbands and recombine it a whole data block. After these process, the cost function has a quadratic form in adaptive filter coefficients, it guarantees the convergence of the suggested block conjugate gradient algorithm. And the block conjugate gradient algorithm which minimizes the suggested cost function has better performance than the case of full-band block conjugate gradient algorithm, the computer simulation results of noise cancellation show the efficiency of the suggested algorithm.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.141-144
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• 2000

스테레오 음향 반향 제거기는 채널신호간에 상호상관(cross-correlation) 때문에 적응필터 계수가 수신실의 반향 경로를 정확하게 추정하지 못한다. 본 논문에서는 상호상관을 줄이기 위해서 채널신호간 차의 절대값과 시변 감쇠상수를 이용하는 새로운 전처리 필터를 제안한다. 시뮬레이션을 통해서 제안하는 전처리 필터가 기존의 방법에 비해서 우수함을 보인다.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.787-788
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• 2006

본 논문에서는 적응적 재구성 필터를 이용한 심전도 신호의 잡음제거 알고리즘을 개발하고 이를 임베디드 보드 상에서 구현하였다. 구현된 시스템의 검증을 위해, 제안된 알고리즘은 PC 상에서 소프트웨어만으로 구현했을 때와 적응적 재구성 필터를 소프트웨어와 FPGA 로 구현했을 때의 실행시간 및 잡음제거 성능을 비교하였다. 실험결과 FPGA 상에서 구현된 시스템은 PC 상에서 구현된 프로그램과 비교하여 동일 잡음제거 성능을 가질 때 약 5배정도의 실행시간 향상을 보였다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.149-152
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• 2000

통신기술의 발달과 정보화 사회로 빠르게 변화되면서, 유선ㆍ무선, 핸즈프리, 원거리 화상회의 등의 다양한 방식의 통신이 이루어지고 있다. 음성통신의 어려운 문제 중에 하나는 주위의 소음이다. 소음은 상황에 따라서 다양하고 복잡하여 그 특성을 분석하기가 어렵다. 소음의 특성과 반향 등을 분석하기 위해서는 수 천 개의 적응필터 탭이 필요하게 된다. 따라서 실시간 소음제거를 위해서는 계산량이 많아 어려움이 따르므로 계산량 감소를 위해 FFT연산에 근거한 주파수 영역의 FDAF 적응필터를 이용하게 되었다. 하지만 계산량은 상당히 감소되었지만, 적응필터의 차수가 증가하면서 시간지연과 하드웨어적으로 복잡하게 되어 블록의 차수를 줄일 수 있는 MDF를 비교 검토하였다.