• 제목/요약/키워드: Bias problem

검색결과 344건 처리시간 0.027초

MNT 시스템에서의 편광소자에 의한 위상오차분석 (Optimization of Modified Triangular Interferometer)

  • 김수길;고명숙
    • 한국조명전기설비학회:학술대회논문집
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    • 한국조명전기설비학회 2007년도 춘계학술대회 논문집
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    • pp.117-119
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    • 2007
  • We need two operation modes to obtain the complex hologram without bias and the conjugate image in the modified triangular interferometer(MTI). To solve the problem, we proposed the optimized MTI with one wave plate, which can obtain cosine and sine functions by the combination of one wave plate and one linear polarizer. In the extraction of phase term using the combination of polarization components, the phase error occurs, and we analyzed such potential phase errors in the optimized MTI.

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불확실성을 갖는 다변수 시스템의 이상검출기법 (Robust fault detection method for uncertain multivariable systems)

  • 홍일선;김대우;권오규
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.710-713
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    • 1996
  • This paper deals with the fault detection problem in uncertain linear multivariable systems having both model mismatch and noise. A robust detection presented by Kwon et al.(1994) for SISO systems has been here extended to the multivariable systems are derived. The model mismatch includes here linearization error as well as undermodelling. Comparisons are made with alternative fault detection method which do not account noise. The new method is shown to have good performance.

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A computed-error-input based learning scheme for multi-robot systems

  • Kuc, Tae-Yong
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.518-521
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    • 1995
  • In this paper, a learning control problem is formulated for cooperating multiple-robot manipulators with uncertain system parameters. The commonly held object is also assumed to be unknown and the multiple-robots themselfs experience uncertain operating conditions such as link parameters, viscous friction parameters, suctions, actuator bias, and etc. Under these conditions, the learning controllers designed for learning of uncertain parameters and robot control inputs for multiple-robot systems are shown to drive the multiple-robot manipulators to follow the desired Cartesian trajectory with the desired internal forces to the unknown object.

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Phase Error due to Polarization Components of the Modified Triangular Interferometer

  • Kim, Soo-Gil
    • Journal of the Optical Society of Korea
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    • 제11권1호
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    • pp.10-17
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    • 2007
  • We need two operation modes to obtain the complex hologram without bias and the conjugate image in the modified triangular interferometer (MTI). To solve the problem, we proposed the optimized MTI with one wave plate, which can obtain cosine and sine functions by the combination of one wave plate and one linear polarizer. In the extraction of phase term using the combination of polarization components, the phase error occurs, and we analyzed such potential phase errors in the optimized MTI.

가속도 바이어스와 타이어반경 오차를 고려한 차량절대속도 추정 (Absolute Vehicle Speed Estimation considering Acceleration Bias and Tire Radius Error)

  • 황진권;송철기
    • 한국자동차공학회논문집
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    • 제10권6호
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    • pp.234-240
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    • 2002
  • This paper treats the problem of estimating the longitudinal velocity of a braking vehicle using measurements from an accelerometer and wheel speed data from standard anti-lock braking wheel speed sensors. We develop and experimentally test three velocity estimation algorithms of increasing complexity. The algorithm that works the best gives peak errors of less than 3 percent even when the accelerometer signal is significantly biased.

Under Water Sonar Transducer Using Terfenol-D Magnetostrictive Material

  • Son, Derac;Cho, Yuk
    • Journal of Magnetics
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    • 제4권3호
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    • pp.98-101
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    • 1999
  • In this work we htave constructed an under water sonar transducer using Terfenol-D rod employing open magnetic circuit. Normally Sonar transducer using Terfenol-D was designed under closed magnetic flux return path, and permanent magnet for dc bias marnetic field, but high magnetic field should be applied to the transducer coil for high sound power and it brings temperature increase inside of the transducer. To improve this heat dissipation problem, we have designed an open magnetic circuit type transducer and we can get 200 dB (re. 1 Pa @ 1m) sound power for the input power of 650 VA.

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실시간 입체 영상 디스플레이를 위한 3차원 공간정합 필터의 합성 (Synthesis of 3-D spatial matched filter for real-time 3-D image display)

  • 임선호;김은수
    • 전자공학회논문지D
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    • 제34D권8호
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    • pp.62-70
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    • 1997
  • In this paper, we presetn a new method to display 3-D image modelled as a sum of 2-D sliced images by expanding the concept of the conventional 2-D optical correlator based on spatial matched filtr to the 3-D region. It is hsown that a arbitrary image can be constructed by an array of the correlation-peaks between pixel-to-pixel and propose the systhesis precedure of 3-D spatial-matched-fjilter using fresnel diffraction equation to display 3-D image in space. It is also shown that the quantization problem is severe when the systehsised filter function is displayed on the conventional LC-SLM. To overcome this problem, anonlinear quantizaton method using the sigmoid function is suggested, and this method can reduce the bias and the loss of high spatial-frequency information, and improve the diffraction efficiency. Finally, the suggested method is tested by computer simulation and then approved by some optical experiments with the conventional LC-SLM.

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Asymmetric Semi-Supervised Boosting Scheme for Interactive Image Retrieval

  • Wu, Jun;Lu, Ming-Yu
    • ETRI Journal
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    • 제32권5호
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    • pp.766-773
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    • 2010
  • Support vector machine (SVM) active learning plays a key role in the interactive content-based image retrieval (CBIR) community. However, the regular SVM active learning is challenged by what we call "the small example problem" and "the asymmetric distribution problem." This paper attempts to integrate the merits of semi-supervised learning, ensemble learning, and active learning into the interactive CBIR. Concretely, unlabeled images are exploited to facilitate boosting by helping augment the diversity among base SVM classifiers, and then the learned ensemble model is used to identify the most informative images for active learning. In particular, a bias-weighting mechanism is developed to guide the ensemble model to pay more attention on positive images than negative images. Experiments on 5000 Corel images show that the proposed method yields better retrieval performance by an amount of 0.16 in mean average precision compared to regular SVM active learning, which is more effective than some existing improved variants of SVM active learning.

레일리 인테그랄의 수치해석상 오차에 대한 이론적 고찰 (Error Analysis Caused by Using the Dftin Numerical Evaluation of Rayleigh's Integral)

  • Kim, Sun-I.
    • 대한의용생체공학회:의공학회지
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    • 제10권3호
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    • pp.323-330
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    • 1989
  • Large bias errors which occur during a numerical evaluation of the Rayleigh's integral is not due to the replicated source problem but due to the coincidence of singularities of the Green's function and the sampling points in Fourier domain. We found that there is no replicated source problem in evaluating the Rayleigh's integral numerically by the reason of the periodic assumption of the input sequence in Dn or by the periodic sampling of the Green's function in the Fourier domain. The wrap around error is not due to an overlap of the individual adjacent sources but berallse of the undersampling of the Green's function in the frequency domain. The replicated and overlApped one is inverse Fourier transformed Green's function rather than the source function.

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하이웨이 네트워크 기반 CNN 모델링 및 사전 외 어휘 처리 기술을 활용한 악성 댓글 분류 연구 (A Study on the Toxic Comments Classification Using CNN Modeling with Highway Network and OOV Process)

  • 이현상;이희준;오세환
    • 한국정보시스템학회지:정보시스템연구
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    • 제29권3호
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    • pp.103-117
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    • 2020
  • Purpose Recently, various issues related to toxic comments on web portal sites and SNS are becoming a major social problem. Toxic comments can threaten Internet users in the type of defamation, personal attacks, and invasion of privacy. Over past few years, academia and industry have been conducting research in various ways to solve this problem. The purpose of this study is to develop the deep learning modeling for toxic comments classification. Design/methodology/approach This study analyzed 7,878 internet news comments through CNN classification modeling based on Highway Network and OOV process. Findings The bias and hate expressions of toxic comments were classified into three classes, and achieved 67.49% of the weighted f1 score. In terms of weighted f1 score performance level, this was superior to approximate 50~60% of the previous studies.