• 제목/요약/키워드: Adaptive noise cancellation

검색결과 118건 처리시간 0.021초

Adaptive Noise Cancellation Based on NLMS Algorithm

  • Li, Shicong;Seo, Ji-Hun;Lee, Seok-Pil
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2014년도 하계학술대회
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    • pp.179-180
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    • 2014
  • The main goal of this paper is to present an adaptive filter system using NLMS(Normalized Least mean square) adaptive algorithm for noise cancellation. The proposed algorithm has less computational complexity and better convergence property than the former algorithms like spectral subtraction algorithm, etc. We use TIMIT criterion voice and Noisex-92 for the experiment. The experimental result shows the feasibility of our algorithm for filtering noise from voice effectively.

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독립성분분석을 이용한 음향 반향 제거 (Acoustic Echo Cancellation Using Independent Component Analysis)

  • 김대성;배현덕
    • 한국음향학회지
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    • 제22권5호
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    • pp.351-359
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    • 2003
  • 본 논문에서는 독립성분분석을 이용한 음향 반향제거 방법을 제안하였다. 음향반향제거기의 마이크로폰에 반향 이외의 잡음이 부가될 경우 반향제거기의 성능은 저하된다. 이러한 문제를 해결하기 위해 본 연구에서는 두 개의 마이크로폰을 이용하여 반향과 선형으로 섞인 잡음을 받은 후 독립성분 분석 기법을 통해 반향과 잡음을 분리하였다. 그리고 분리된 반향 신호를 반향제거기에 사용되는 적응 알고리듬의 기준 신호로 이용함으로서 반향제거기의 성능을 향상시켰다. 컴퓨터 모의실험을 통해 제안한 방법의 타당성을 확인하였다.

심전도 신호의 잡음 제거를 위한 적응 필터 (Adaptive Filter for Noise Cancellation of ECG's)

  • 이재준;송철규;이제석;이명호
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1992년도 춘계학술대회
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    • pp.186-189
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    • 1992
  • Adaptive fliter for noise cancellation of ECG is proposed. An adaptive noise canceller using the least mean squares algorithm is used to reduce unwanted noise. The adaptive noise canceller minimizes the mean-square error between a primary input, which is the noisy ECG, and a reference input, which is either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input.

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기어박스에서의 베어링 결함 진단 (Bearing Fault Diagnostics in a Gearbox)

  • 김흥섭;이상권
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 추계학술대회논문집
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    • pp.611-616
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    • 2002
  • Bearing diagnostics is difficult in a gearbox because bearing signals are masked by the strong gear signals. Self adaptive noise cancellation(SANC) is useful technique to seperate bearing signals from gear signals. While gear signals are correlated with a long correlation length, bearing signals are not correlated with a short length. SANC seperates two components on the basis of correlation length. Then we can find defect frequency component in the envelope spectrum of the bearing signals.

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기어 박스에서의 베어링 결함 진단 (Bearing Falut Diagnostics in a Gearbox)

  • Kim, Heung-Sup;Lee, Sang-Kwon
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 추계학술대회논문초록집
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    • pp.362.2-362
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    • 2002
  • Bearing diagnostics is difficult in a gearbox because bearing signals are masked by the strong gear signals. Self adaptive noise cancellation(SANC) Is useful technique to seperate bearing signals from gear signals. While gear signals are correlated with a long correlation length, bearing signals are not correlated with a short length. SANC seperates two components on the basis of correlation length. (omitted)

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Speech Noise Cancellation using Time Adaptive Threshold Value in Wavelet Transform

  • Lee Chul-Hee;Lee Ki-Hoon;Hwang Hyang-Ja;Moon In-Seob;Kim Chong-Kyo
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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    • pp.244-248
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    • 2004
  • This paper proposes a new noise cancellation method for speech recognition in noise environments. We determine the time adaptive threshold value using standard deviations of wavelet coefficients after wavelet transform by frames. The time adaptive threshold value is set up by using sum of standard deviations of wavelet coefficients in cA3 and weighted cD1. cA3 coefficients represent the voiced sound with lower frequency components and cD1 coefficients represent the unvoiced sound with higher frequency components. In experiments, we removed noise after adding white Gaussian noise and colored noise to original speech. The proposed method improved SNR and MSE more than wavelet transform and wavelet packet transform does. As a result of speech recognition experiment using noise speech DB, recognition performance is improved by $2\sim4\;\%.$

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부밴드 블록 공액 경사 알고리듬을 이용한 음향잡음 제거 (An Acoustic Noise Cancellation Using Subband Block Conjugate Gradient Algorithm)

  • 김대성;배현덕
    • 한국음향학회지
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    • 제20권3호
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    • pp.8-14
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    • 2001
  • 본 논문에서는 부밴드 적응 필터 구조에서 음향 신호에 부가된 잡음을 제거하기 위한 새로운 비용함수와 블록 공액 경사 알고리듬을 제안하였다. 제안한 비용함수를 위하여 부밴드로 나뉘는 신호를 블록으로 구성한 후 각 대역에서의 신호를 하나의 블록으로 조합하였다. 이러한 과정을 통해 제시된 비용함수는 부밴드 적응 필터 구조에서 적응 필터에 대한 2차 형식을 가짐으로서 제안한 알고리듬의 수렴성이 보장되었다. 또한 제안한 비용함수를 최소화하는 알고리듬으로 사용한 부밴드 블록 공액 경사 알고리듬은 전대역 블록 공액 경사 알고리듬에 비해 잡음제거 성능이 뛰어난 것을 컴퓨터 모의 실험으로 확인하였다.

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제어오차계의 가중치를 이용한 차실내 능동소음제어 시스템 연구 (A Study on the Active Noise Cancellation System in a Vehicle Cabin Using the Weighting Factors of Control Error Path)

  • 홍석윤;허현무
    • 소음진동
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    • 제6권6호
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    • pp.851-856
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    • 1996
  • The active noise cancellation system showing the effective convergence and stability has been studied by simplifying the controller structures using the weighting factors of control error path to the multi-channel filtered-x LMS algorithm which needs a lot of calculations and the performance has been verified experimentally. Besides, to implement the system performance in a vehicle cabin, experimental work for selecting the suitable numbers and positions of the microphones and speakers was accomplished. Effectively combining a TMS 320C 31 main processor conducting real number calculations and having various functions with other components, the purpose-built system board for active noise cancellation has been designed and with this board, car active noise cancellation system showing maximum stable 10dB noise reduction has been obtained at the car idling conditions above 3000rpm range.

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적응모델을 이용한 단일채널 능동 소음제어 (Single Channel Active Noise Control using Adaptive Model)

  • 김영달;이민명;정창경
    • 대한전기학회논문지:시스템및제어부문D
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    • 제49권8호
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    • pp.442-450
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    • 2000
  • Active noise control is an approach to noise reduction in which a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and a time-adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Opppenheim model assumed that transfer function characteristics from the canceling source to the error sensor is only propagation delay. But this paper proposes a modified Oppenheim model by considering transfer characteristics of acoustic device and noise path. This transfer characteristics is adaptively cancelled by adaptive model. This is proved by computer simulation with artifically generated random noise and sine wave noise. The details of the proposed architecture, and theoretical simulation and experimental results of the noise cancellation system for three dimension enclosure are presented in the paper.

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