• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.179-182
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• 2004

무선통신분야에서 LMS5(Least Mean Square) 알고리즘은 식이 간단하고 계산량이 비교적 적기 때문에 널리 사용되고 있다. 그러나 시간영역에서 처리할 경우 입력신호의 고유치 변동폭이 넓게 분포되어 수렴속도가 저하하는 문제점이 있다. 이를 해결하기 위하여 신호를 FFT(Fast Fourier Trasnform)나 DCT(Discrete Cosine Transform)로 변환하여 신호간의 상관도를 제거함으로써 시간영역에서 LMS알고리즘을 적용할 때 보다 수렴속도를 크게 향강시킬 수 있다. 본 논문에서는 수렴속도 향상을 위해 시간영역의 적응 알고리즘을 직교변환인 고속웨이브렛(wavelet)변환을 이용하여 변환영역에서 수행하며, 짧은 필터계수를 가지는 DWT(Discrete Wavelet Transform)특성에 맞는 Fast running FIR 알고리즘을 이용하여 WTLMS(Wavelet Transform LMS)적응알고리즘을 통신시스템에 적용한다. 적응 알고리즘의 성능향상을 위하여 시간에 따라 적응상수의 크기를 가변시켜 수렴 초기에는 큰 적응상수로 따른 수렴이 가능하도록 하고 점차 적응상수의 크기를 줄여서 misadjustment도 줄이는 방법의 적응 알고리즘을 제안하였다. 제안한 알고리즘을 실제로 적응잡음제거기(adaptive noise canceler)에 적용하여 컴퓨터 시뮬레이션을 하였으며, 각 알고리즘들의 계산량, 수렴속도를 이용하여 각각 비교, 분서하여 그 성능이 우수함을 입증하였다.

• 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.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1203-1210
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• 1999

Coefficients of the adaptive filter are misadjusted by primary signals which are uncorrelated with reference signals of the adaptive filter. In this paper, the normalized sign algorithm is analyzed and compared with the NLMS algorithm by the steady state performance and the transient characteristics when target signals are included in primary signals. The excess mean square error of the NLMS algorithm is proportional to the power of target signals. That of normalized sign algorithm is proportional to the square root of the target signal power. However, the convergence speed of the normalized sign algorithm is slower than that of NLMS algorithm. In this paper, it is shown that theoretical analysis of the steady state performance and the transient characteristics are well consisted with the results of computer simulation.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.195-202
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• 2014

The Global Positioning System (GPS), which has various military and commercial applications, is designed to estimate the location of the specific user or object. In order to accurately estimate the location, GPS requires at least four satellite signals. The GPS receiver operates on extremely low signal-to-noise ratio (SNR) environment and it may suffer from various interference signals with the extremely high power. In this paper, we introduce a blind adaptive receiver based on the modified despreader, which suppress interference signals and detect GPS signals of interest without requiring explicit angle-of-arrival (AOA) information. We, also, provide the mathematical analysis for the signal-to-interference and noise ratio (SINR) of the modified despeader beamformer output. A representative computer simulation example is presented to illustrate the interference suppression performance of the considered GPS receiver and mathematical analysis of the SINR.

• 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.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.