• 제목/요약/키워드: Process-error model

검색결과 1,158건 처리시간 0.026초

개선된 S-curve 모델과 RGB 칼라 참조표를 이용한 모니터와 모바일 디스플레이 장치간 색 정합 (Color matching between monitor and mobile display device using improved S-curve model and RGB color LUT)

  • 박기현;이명영;이철희;하영호
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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    • pp.15-18
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    • 2003
  • This paper proposes a color matching 3D look-up table simplifying the complex color matching procedure between a monitor and a mobile display device. In order to perform color matching, it is necessary to process color of image in the device independent color space like CIEXYZ or CIELAB. We improved the S-curve model to have smaller characterization error than tolerance error. Also, as a result of the experiments, we concluded that the color matching look-up table with 64(4$\times$4$\times$4) is the smallest size allowing characterization error to be acceptable.

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Times Series Analysis of GPS Receiver Clock Errors to Improve the Absolute Positioning Accuracy

  • Bae, Tae-Suk;Kwon, Jay-Hyoun
    • 한국측량학회지
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    • 제25권6_1호
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    • pp.537-543
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    • 2007
  • Since the GPS absolute positioning with pseudorange measurements can significantly be affected by the observation error, the time series analysis of the GPS receiver clock errors was performed in this study. From the estimated receiver clock errors, the time series model is generated, and constrained back in the absolute positioning process. One of the CORS (Continuously Operating Reference Stations) network is used to analyze the behavior of the receiver clock. The dominant part of the model is the linear trend during 24 hours, and the seasonal component is also estimated. After constraining the modeled receiver clock errors, the estimated position error compared to the published coordinates is improved from ${\pm}11.4\;m\;to\;{\pm}9.5\;m$ in 3D RMS.

수도권 영역의 시간 후방 모드 WRF-FLEXPART 모의를 위한 입자 수에 따른 무작위 오차의 정량 분석 (Quantitative Analysis of Random Errors of the WRF-FLEXPART Model for Backward-in-time Simulation over the Seoul Metropolitan Area)

  • 우주완;이재형;이상현
    • 대기
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    • 제29권5호
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    • pp.551-566
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    • 2019
  • Quantitative understanding of a random error that is associated with Lagrangian particle dispersion modeling is a prerequisite for backward-in-time mode simulations. This study aims to quantify the random error of the WRF-FLEXPART model and suggest an optimum number of the Lagrangian particles for backward-in-time simulations over the Seoul metropolitan area. A series of backward-in-time simulations of the WRF-FLEXPART model has conducted at two receptor points by changing the number of Lagrangian particles and the relative error, as a quantitative indicator of random error, is analyzed to determine the optimum number of the release particles. The results show that in the Seoul metropolitan area a 1-day Lagrangian transport contributes 80~90% in residence time and ~100% in atmospheric enhancement of carbon monoxide. The relative errors in both the residence time and the atmospheric concentration enhancement are larger when the particles release in the daytime than in the nighttime, and in the inland area than in the coastal area. The sensitivity simulations reveal that the relative errors decrease with increasing the number of Lagrangian particles. The use of small number of Lagrangian particles caused significant random errors, which is attributed to the random number sampling process. For the particle number of 6000, the relative error in the atmospheric concentration enhancement is estimated as -6% ± 10% with reduction of computational time to 21% ± 7% on average. This study emphasizes the importance of quantitative analyses of the random errors in interpreting backward-in-time simulations of the WRF-FLEXPART model and in determining the number of Lagrangian particles as well.

HMM-Based Transient Identification in Dynamic Process

  • Kwon, Kee-Choon
    • Transactions on Control, Automation and Systems Engineering
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    • 제2권1호
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    • pp.40-46
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    • 2000
  • In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

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GMAW에서 비드형상제어에 관한 연구 (Control of Bead Geometry in GMAW)

  • 이재범;방용우;오성원;장희석
    • Journal of Welding and Joining
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    • 제15권6호
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    • pp.116-123
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    • 1997
  • In GMA welding processes, bead contour and penetration patterns are criterion to estimate weld quality. Bead geometry is commonly defined with width, height and depth. When weaving is taken into account, selection of welding conditions is known to be difficult. Thus, empirical or trial-and-error method are usually introduced. This study examined the correlation of welding process variables including weaving parameters with bead geometry using srtificial neural networks(ANN). The main task of the Ann estimator is to realize the mapping characteristics from the sampled welding process variables to the actual bead geometry through training. After the neural network model is constructed, welding process variables for desired bead geometry is selected by inverse model. Experimental varification of the inverse model is conducted through actual welding.

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Decision-Tree-Based Markov Model for Phrase Break Prediction

  • Kim, Sang-Hun;Oh, Seung-Shin
    • ETRI Journal
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    • 제29권4호
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    • pp.527-529
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    • 2007
  • In this paper, a decision-tree-based Markov model for phrase break prediction is proposed. The model takes advantage of the non-homogeneous-features-based classification ability of decision tree and temporal break sequence modeling based on the Markov process. For this experiment, a text corpus tagged with parts-of-speech and three break strength levels is prepared and evaluated. The complex feature set, textual conditions, and prior knowledge are utilized; and chunking rules are applied to the search results. The proposed model shows an error reduction rate of about 11.6% compared to the conventional classification model.

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최적의 FEC 부호율 결정을 위한 정확한 채널손실 한계집합 추정기법 (An Accurate Estimation of Channel Loss Threshold Set for Optimal FEC Code Rate Decision)

  • 정태준;정요원;서광덕
    • 방송공학회논문지
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    • 제19권2호
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    • pp.268-271
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    • 2014
  • 소스 부호 왜곡 모델 및 채널 유도 왜곡 모델 기반의 기존의 FEC 부호율 결정 기법들은 일반적으로 높은 계산 복잡도와 구현 비용을 요구하는 모델 파라메터 트레이닝 과정을 요구한다. 본 논문에서는 복잡한 모델링 과정을 피하기 위해서 최적의 FEC 부호율 결정을 위한 채널 손실 한계집합을 추정하기 위한 정확한 소스-채널 결합 왜곡 모델을 제안한다.

An INS Filter Design Considering Mixed Random Errors of Gyroscopes

  • Seong, Sang-Man;Kang, Ki-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.262-264
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    • 2005
  • We propose a filter design method to suppress the effect of gyroscope mixed random errors at INS system level. It is based on the result that mixed random errors can be represented by a single equivalent ARMA model. At first step, the time difference of equivalent ARMA process is performed, which consider the characteristic of indirect feedback Kalman filter used in INS filter. Next, a state space conversion of time differenced ARMA model is achieved. If the order of AR is greater than that of MA, the controllable or observable canonical form is used. Otherwise, we introduce the state equation of which the state variable is composed of the ARMA model output and several step ahead predicts of that. At final step, a complete form state equation is presented. The simulation results shows that the proposed method gives less transient error and better convergence compared to the conventional filter which assume the mixed random errors as white noise.

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동승석 에어백 핵심 성능 인자 및 상해위험도 예측 기법 개발에 대한 연구 (A Study on the Key Performance Factors of Passenger Airbag and Injury Risk Prediction Technique Development)

  • 박동규
    • 한국자동차공학회논문집
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    • 제21권5호
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    • pp.130-135
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    • 2013
  • Until now, passenger airbag design is based on the referred car design and many repetitive crash tests have been done to meet the crash performance. In this paper, it was suggested a new design process of passenger airbag. First, key performance factors were determined by analyzing the injury risk effectiveness of each performance factor. And it was made a relationship between injury risk and performance factor by using the response surface model. By using this one, it can be predicted the injury risk of head and neck. Predicted injury risk of optimal design was obtained through this injury risk prediction model and it was verified by FE analysis result within 18% error of head and 9% error of neck. It was shown that a target crash performance can be met by controlling the key performance factors only.

결함 제거의 실패를 고려하는 소프트웨어 신뢰도 모델 (A Software Reliability Growth Model with Probability of Imperfect Debugging)

  • 김영휘;김성인;이원형
    • 대한산업공학회지
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    • 제18권1호
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    • pp.37-45
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    • 1992
  • Common assumption we frequently encounter in early models of software reliability is that no new faults are introduced during the fault removal process. In real life, however, there are situations in which new faults are introducted as a result of imperfect debugging. This study alleviating this assumption by introducting the probability of perfect error-correction is an extension of Littlewood's work. In this model, the system reliability, failure rates, mean time to failure and average failure frequency are obtained. Here, when the probability of perfect error-correction is one, the results appear identical with those of the previous studies. In the respect that the results of previous studies are special cases of this model, the model developed can be considered as a generalized one.

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