• 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.

• 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.

• 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.

• The Journal of the Acoustical Society of Korea
• /
• 제17권3E호
• /
• pp.58-66
• /
• 1998

In this paper, we analyze the effects of interference canceller on the performance of multitone DS/CDMA system proposed by Vandendorpe[5]. There are various kinds of interference canceller suggested by different researchers including parallel and successive cancellers and we adopt a canceller used by Yoon et al.[9] which is a kind of parallel canceller. We consider three kinds of interferences, that is, multipath interference(MPI), interchannel interference(ICI) and multiple access interference(MAI). The ICI is the interference between multitones. The equations for variances. are derived for the inteferences and thermal noise used for signal to noise ratio calculation. We also consider RAKE reception over multipath channel which is modeled as lowpass equivalent linear filter and three stage interference canceller used for performance improvement. We show the performance results for number of canceller stage, diversity order and number of users and draw some conclusions that interference canceller is effective in multitone DS/CDMA system and the performance is further improved with the higher order of diversity and larger number of PN chips.

• 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.

• 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.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1996년도 하계학술대회 논문집 B
• /
• pp.1066-1068
• /
• 1996

This paper concerns about the active noise canceller via filtered-X LMS algorithm. There are various kinds of algorithms to implement a active noise canceller. Traditional LMS algorithms are not enough to implement a sharp noise cancellation characteristics. We simulates a filtered-X LMS algorithm and implements an algorithm to the TMS320C5x DSP processor and shows that result.

• 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.

• 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.

• ETRI Journal
• /
• 제38권2호
• /
• pp.366-375
• /
• 2016

This paper describes an algorithm to suppress composite noise in a two-microphone speech enhancement system for robust hands-free speech communication. The proposed algorithm has four stages. The first stage estimates the power spectral density of the residual stationary noise, which is based on the detection of nonstationary signal-dominant time-frequency bins (TFBs) at the generalized sidelobe canceller output. Second, speech-dominant TFBs are identified among the previously detected nonstationary signal-dominant TFBs, and power spectral densities of speech and residual nonstationary noise are estimated. In the final stage, the bin-wise output signal-to-noise ratio is obtained with these power estimates and a Wiener post-filter is constructed to attenuate the residual noise. Compared to the conventional beamforming and post-filter algorithms, the proposed speech enhancement algorithm shows significant performance improvement in terms of perceptual evaluation of speech quality.