• 제목/요약/키워드: Noise Removal

검색결과 503건 처리시간 0.031초

강체롤과 접촉 회전하는 브러시롤의 진동 현상 (Vibration Behavior of a Rotating Brush Roll in Contact with a Solid Roll)

  • 허주호
    • 소음진동
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    • 제7권3호
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    • pp.499-509
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    • 1997
  • During the process of oxide removal from work rolls in sheet metal manufacture, filamentary brushes frequently exhibit a bouncing or chatter behavior. The dynamics of this phenomenon is investigated through the development of expressions for the non-linear contact stiffness between the brush and the roll. With formulation of simple structural models, the time responses in the presence and absence of friction under random excitation are investigated. Possible solutions for the minimization or avoidance of this bouncing or chatter problem are also suggested.

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Laser Treatment in Restorative Dentistry

  • Shintani, Hideaki
    • 대한치과보존학회:학술대회논문집
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    • 대한치과보존학회 2001년도 추계학술대회(제116회) 및 13회 Workshop 제3회 한ㆍ일 치과보존학회 공동학술대회 초록집
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    • pp.556-556
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    • 2001
  • The application of the laser to the tooth hard tissue started from the removal of carious dentin with the laser performed by Goldman in 1964. With the development of the laser technology, the laser treatment with less descomfort such as pain, vibration, and noise, etc. has been attempted. Since it is difficult to give a suitable form for inlay restoration to a cavity prepared with laser, it has to be restored with adhesive resinous materials. However, various evaluation of adhesive properties of the resinous materials to lased tooth surface on the various conditions such as adgerent, irradiation condition, procedure of bond test, and adhesive materials used, etc. have been reported.(omitted)

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CHIP 영상으로부터의 CIF 추출 (CIF Extraction from Chip Image)

  • 김지홍;김남철;정호선
    • 대한전자공학회논문지
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    • 제25권9호
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    • pp.1081-1090
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    • 1988
  • A series of procedures using image processing techniques is presented for extracting layout information fast and automatically from chip images. CIF (caltech intermediate form) is chosen for representing such information. First, line-edges are extracted using a line-edge detector. Then, thinning and noise removal procedures follow. Subsequent procedures are vertex extraction and vertex grouping. Finally, CIF is extracted from the coordinates of the grouped vertices. In this paper, the final process is applied to only metal layer. In experiments, this processing scheme is shown to be very effective in extracting CIF.

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Bayesian 방법에 의한 잡음감소 방법에 관한 연구 (Wavelet Denoising based on a Bayesian Approach)

  • 이문직;정진현
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 G
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    • pp.2956-2958
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    • 1999
  • The classical solution to the noise removal problem is the Wiener filter, which utilizes the second-order statistics of the Fourier decomposition. We discuss a Bayesian formalism which gives rise to a type of wavelet threshold estimation in non-parametric regression. A prior distribution is imposed on the wavelet coefficients of the unknown response function, designed to capture the sparseness of wavelet expansion common to most application. For the prior specified, the posterior median yields a thresholding procedure

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외곽선 검출 및 잡음 제거 알고리즘 (Edge detection and noise removal algorithm)

  • 문우혁;정시훈
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2021년도 추계학술발표대회
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    • pp.945-947
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    • 2021
  • Canny Edge Detection은 필터와 방향벡터를 이용한 대표적인 외곽선 추출 알고리즘으로서 대부분의 외곽선 추출 연구에서 이를 변형하여 사용한다. 그러나 본 논문에서는 외곽선 추출의 전처리 과정으로서 이미지에서의 잡음을 제거하는 알고리즘과 이를 바탕으로 외곽선을 더욱 효율적으로 추출할 수 있는 독창적인 알고리즘을 제시한다.

Identification of plastic deformations and parameters of nonlinear single-bay frames

  • Au, Francis T.K.;Yan, Z.H.
    • Smart Structures and Systems
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    • 제22권3호
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    • pp.315-326
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    • 2018
  • This paper presents a novel time-domain method for the identification of plastic rotations and stiffness parameters of single-bay frames with nonlinear plastic hinges. Each plastic hinge is modelled as a pseudo-semi-rigid connection with nonlinear hysteretic moment-curvature characteristics at an element end. Through the comparison of the identified end rotations of members that are connected together, the plastic rotation that furnishes information of the locations and plasticity degrees of plastic hinges can be identified. The force consideration of the frame members may be used to relate the stiffness parameters to the elastic rotations and the excitation. The damped-least-squares method and damped-and-weighted-least-squares method are adopted to estimate the stiffness parameters of frames. A noise-removal strategy employing a de-noising technique based on wavelet packets with a smoothing process is used to filter out the noise for the parameter estimation. The numerical examples show that the proposed method can identify the plastic rotations and the stiffness parameters using measurements with reasonable level of noise. The unknown excitation can also be estimated with acceptable accuracy. The advantages and disadvantages of both parameter estimation methods are discussed.

DSP를 이용한 자동차 소음에 강인한 음성인식기 구현 (Implementation of a Robust Speech Recognizer in Noisy Car Environment Using a DSP)

  • 정익주
    • 음성과학
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    • 제15권2호
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    • pp.67-77
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    • 2008
  • In this paper, we implemented a robust speech recognizer using the TMS320VC33 DSP. For this implementation, we had built speech and noise database suitable for the recognizer using spectral subtraction method for noise removal. The recognizer has an explicit structure in aspect that a speech signal is enhanced through spectral subtraction before endpoints detection and feature extraction. This helps make the operation of the recognizer clear and build HMM models which give minimum model-mismatch. Since the recognizer was developed for the purpose of controlling car facilities and voice dialing, it has two recognition engines, speaker independent one for controlling car facilities and speaker dependent one for voice dialing. We adopted a conventional DTW algorithm for the latter and a continuous HMM for the former. Though various off-line recognition test, we made a selection of optimal conditions of several recognition parameters for a resource-limited embedded recognizer, which led to HMM models of the three mixtures per state. The car noise added speech database is enhanced using spectral subtraction before HMM parameter estimation for reducing model-mismatch caused by nonlinear distortion from spectral subtraction. The hardware module developed includes a microcontroller for host interface which processes the protocol between the DSP and a host.

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ST세그먼트 검출성능향상을 종속 적응필터의 세계 (Design of a Cascade Adaptive Filter for the Performance sn Detection of Segment)

  • 박광리;이경중
    • 대한의용생체공학회:의공학회지
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    • 제16권4호
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    • pp.517-524
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    • 1995
  • This paper is a study on the design of the cascade adaptive filter (CAF) for baseline wandering elimination in order to enhance the performance of the detection of ST segments in ECG. The CAF using Least Mean Square (LMS) algorithm consists of two filters. The primary adaptive filter which has the cutoff frequency of 0.3Hz eliminates the baseline wandering in raw ECG The secondary adaptive filter removes the remnant baseline wandering which is not eliminated by the primary adaptive filter. The performance of the CAF was compared with the standard filter, the recursive filter, and the adaptive impulse correlated filter (AICF). As a result, the CAF showed a lower signal distortion than the standard filter and the AICF. Also, the CAF showed a better perf'ormance in noise elimination than the standard filter and the recursive filter. In conclusion, considering the characteristics of the noise elimination and the signal distortion, the CAF shows a better performance in the removal of the baseline wandering than the other three Otters and suggests the high performance in the detection of ST segment.

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AWGN에 훼손된 영상에서 국부 마스크의 화소 분포를 이용한 잡음 제거에 관한 연구 (A Study on Noise Removal using Pixel Distribution of Local Mask in Degraded Image by AWGN)

  • 권세익;황용연;김남호
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2015년도 추계학술대회
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    • pp.933-935
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    • 2015
  • 현재, 영상처리는 다양한 분야에서 활용되고 있으며, 영상을 전송, 처리, 저장하는 과정에서 발생하는 잡음을 제거하기 위해, 영상복원에 관한 많은 연구가 진행되고 있다. 영상에 첨가되는 잡음은 발생원인과 형태에 따라 다양한 종류가 있으며, AWGN(additive white Gaussian noise)이 대표적이다. 본 논문에서는 영상에 첨가된 AWGN을 완화하기 위해, 국부 마스크내의 중심화소와 주변화소의 차이에 따라 가중치를 다르게 적용하는 알고리즘을 제안하였다.

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시선 추적 센서 데이터를 활용한 뇌파 잡파 제거 방법에 관한 연구 (A Study on EEG Artifact Removal Method using Eye tracking Sensor Data)

  • 윤종섭;김진헌
    • 전기전자학회논문지
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    • 제22권4호
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    • pp.1109-1114
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    • 2018
  • 뇌파(Electroencephalogram, EEG)는 외부 자극 때문에 발생하는 뇌 활동을 연구하기 위해 사용되는 도구로 두피에 전극을 부착하여 기록한다. 이 과정에서 잡파(artifact)가 혼입되어 신호를 왜곡시키기 쉬워 이를 제거하기 위한 후처리가 필수적이다. 잡파 제거를 위해 널리 사용되는 방법으로 독립성분분석(Independent Component Analysis, ICA)이 존재한다. 이 방법은 성능은 우수하나 뇌파 정보를 일부 손실시키는 단점이 있다. 본 논문에서는 이러한 문제점을 보완하기 위해 시선 추적 센서(Eyetracker)를 통해 얻은 눈 깜빡임 정보를 이용하여 필터 적용 범위를 제한함으로써 뇌파 정보 손실을 줄이는 방법을 제안한다. 이후 신호 대 잡음 비(Signal to Noise Ratio, SNR), 스펙트럼 일관성(Spectral Coherence, SC) 등의 정량화 방법을 이용하여 기존의 방법과 제안하는 방법의 결과를 비교하였다.