• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 1998년도 추계종합학술대회 논문집
• /
• pp.1183-1186
• /
• 1998

Adaptive nois canceller can extract the noiseremoved spech in noisy speech signal by adapting the filter-coefficients to the background noise environment. A kind of LMS algorithm is one of the most popular adaptive algorithm for noise cancellation due to low complexity, good numerical property and the merit of easy implementation. However there is the matter of increasing misadjustment at voiced speech signal. Therefore the demanded speech signal may be extracted. In this paper, we propose a fast and noise robust wavelet packet adaptive noise canceller with NLMS-SUM method LMS combined algorithm. That is, we decompose the frequency of noisy speech signal at the base of the proposed analysis tree structure. NLMS algorithm in low frequency band can efficiently dliminate the effect of the low frequency noise and SUM method LMS algorithm at each high frequency band can remove the high frequency nosie. The proposed wavelet packet adaptive noise canceller is enhanced the more in SNR and according to Itakura-Satio(IS) distance, it is closer to the clean speech signal than any other previous adaptive noise canceller.

• 한국통신학회논문지
• /
• 제22권10호
• /
• pp.2339-2347
• /
• 1997

The performance of the adaptive noise canceller using LMS algorithm is degraded by the gradient noise due to target speech signals. An adaptive noise canceller with speech detector was proposed to reduce this performande degradation. The speech detector utilized the adaptive prediction-error filter adapted by the NLMS algorithm. This paper discusses to enhance the performance of the adaptive noise canceller forthecorlored noise. The affine projection algorithm, which is known as faster than NLMS algorithm for correlated signals, is used to adapt the adaptive filter and the adaptive prediction error filter. When the voice signals are detected by the speech detector, coefficients of adaptive filter are adapted by the sign-error afine projection algorithm which is modified to reduce the miaslignment of adaptive filter coefficients. Otherwirse, they are adapted by affine projection algorithm. To obtain better performance, the proper step size of sign-error affine projection algorithm is discussed. As resutls of computer simulation, it is shown that the performance of the proposed ANC is better than that of conventional one.

• 한국음향학회:학술대회논문집
• /
• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
• /
• pp.873-878
• /
• 1994

Application of the filtered-x LMS adaptive filter to active noise cancellation requires to estimate the transfer characteristics between the output and the error signal of the adaptive canceller. We analyze the effects of estimation accuracy on the convergence behavior of the canceller when the input noise is modeled as a sinusoid.

• 음성과학
• /
• 제8권2호
• /
• pp.73-81
• /
• 2001

In this paper, we focus on the real time implementation of the single channel adaptive noise canceller(ANC) by using TMS320C30 EVM board. The implemented single channel adaptive noise canceller is based on a reference paper [1] in which it is simulated by using the recursive average magnitude difference function(AMDF) to get a properly delayed input speech on a sample basis as a reference signal and normalized least mean square(NLMS) algorithm. To certify results of the real time implementation, we measured the processing time of the ANC and enhancement ratio according to various signalto-noise ratios(SNRs). Experimental results demonstrate that the processing time of the speech signal of 32ms length with delay estimation of every 10 samples is about 26.3 ms, and almost the same performance as given in [1] is obtained with the implemented system.

• 한국항행학회논문지
• /
• 제13권4호
• /
• pp.482-489
• /
• 2009

이 논문에서는 AWGN환경에서 발생하는 가우시안 잡음과 발진기에서 생기는 시스템 잡음을 제거할 수 있는 ALE(Adaptive Line Enhancer) 기반의 새로운 적응형 잡음 제거기를 이용한 CW(Continuous-Wave) 바이오 레이더를 제안한다. 최근에 CW 바이오 레이더를 이용해서 심장박동과 호흡을 검출하는 연구가 여러 연구기관에서 진행 되고 있다. 그러나 이 연구들은 기존 CW 바이오 레이더가 가우시안 잡음에 취약하고 그로 인해 심장박동 검출정확도도 떨어진다는 점을 설명을 하고 있긴 하지만, 그 잡음을 효과적으로 없앨 수 있는 방안은 계속 연구 중에 있다. 본 논문에서는 기저대역 신호에 포함된 잡음을 효과적으로 제거할 수 있는 ALE기반의 적응형 잡음 제거기를 적용한 것을 제안한다. 또한 타겟의 위치에 따른 복조의 민감함에 강점을 가진 quadrature 수신기를 통과한 잡음이 포함된 기저대역 신호에서 잡음만을 효과적으로 제거함으로 인해 심장박동 검출 정확도를 향상시키는 것을 모의실험을 통해 비교 분석해 본다.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2004년도 추계학술대회 논문집
• /
• pp.345-351
• /
• 2004

This Paper describes a nonlinear adaptive noise filter using neural network for digital controller system. Back-Propagation Learning Algorithm based MLP (Multi Layer Perceptron)is used an adaptive filters. In this paper. it assume that the noise of primary input in the adaptive noise canceller is not the same characteristic as that of the reference input. Experimental reaults show that the neural network base noise canceller outperforms the linear noise canceller. Especially to make noise cancel close to realtime, Primary input is divided by unit and each divided part is processed for very short time than all the processed data are unified to whole data.

• Journal of information and communication convergence engineering
• /
• 제8권6호
• /
• pp.640-644
• /
• 2010

When we talk with hands-free in a car or noisy lobby, the performance of the echo canceller degrade because background noise added to echo caused by the distance from mouth to microphone is relatively long. It gives a reason for necessity of noise-robust and high convergence speed adaptive algorithm. And if acoustic echo canceller operated not perfectly, residual signal going through the echo canceller to far-end speaker remains residual echo, which degrade quality of talk. To solve this problem, post-processing needed to remove residual echo ones more. In this paper, we propose a new acoustic echo canceller, which has noise robust and high convergence speed, linked with linear predictor as a post-processor. By computer simulation, it is confirmed that the proposed algorithm shows better performance from acoustic interference cancellation (AIC) viewpoint.

• 한국통신학회논문지
• /
• 제16권12호
• /
• pp.1219-1228
• /
• 1991

적응 필터를 이용한 잡음제거기 모형은 실제의 경우 잡음신호원 으로부터 주신호입력까지 경로 전달함수와 잡음제거기의 잡음신호입력 까지의 경로 전달함수가 모두 존재한다. 종래의 잡음제거기 모형에서 한쪽의 경로 전달함수만을 고려한점을 개선하여 제안된 새 모형에서 두 방향의 전달함수가 모두 존재하는 것으로 하여 적응 잡음제거기의 최적 전달함수를 유도하였다. 적응 필터는 적응 속도가 빠른 JP 격자필터를 이용하였고 ANC-ALE 모형에 의해 SNR이 더욱 개선됨을 나타내었으며 시뮬레이션을 통하여 확인하였다. 아울러 dc bias가 특별한 신호에 대해 잡음제거기에 더욱 효과적으로 작용함을 보였다.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2003년도 추계학술대회
• /
• pp.125-130
• /
• 2003

This Paper describes a Nonlinear adoptive noise canceller using Neural Network for Machine Tools Controller System. Back-Propagation Learning Algorithm based MLP (Multi Layer Perceptron)is used an adaptive filters. In this Paper. it assume that the noise of primary input in the adaptive noise canceller is not the same characteristic as that of the reference input. Experimental results show that the neural network base noise canceller outperforms the linear noise canceller. Especially to make noise cancel close to realtime, Primary Input is divided by Unit and each divided pan is processed for very short time than all the processed data are unified to whole data.

• 대한전자공학회논문지
• /
• 제27권9호
• /
• pp.1456-1467
• /
• 1990

The time domain adaptive noise canceller (time domain ANC) with the adaptive compensator and its algorithm, so called compensated least mean squares(CLMS) algorithm, had been introduced to improve the performance of ANC[1]. In this paper the time domain ANC with the adaptive compensator is transformed into the frequency domain ANC with the adaptive ocmpensator. An compensated frequency-domain least mean squares(CFLMS) algorithm that can adapt the proposed frequency domain ANC is presented.