• 제목/요약/키워드: Error estimator

검색결과 658건 처리시간 0.023초

다중 채널 환경에서 터보 등화기 성능 분석 (Performance Analysis of Turbo Equalizer in the Multipath Channel)

  • 정지원
    • 한국정보전자통신기술학회논문지
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    • 제5권3호
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    • pp.169-173
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    • 2012
  • 무선통신 시스템에서 신호의 다중경로 전달 과정에 의해 발생하는 지연 확산 현상 때문에 인접 심벌 간 간섭 (ISI, Inter-Symbol Interference)에 영향을 받는다. 본 논문에서는 다중 경로를 갖는 채널에서 채널 부호화 기법과 등화기가 결합하여 동작하는 터보 등화기를 갖는 시스템의 성능을 검증하였다. 그 결과 본 논문에서 사용한 터보 등화기를 이용하여 반복 복호를 하였을 때는, 1회 반복 시 BER 10-4을 기준으로 반복이 없는 등화기를 사용하였을 때 보다 1.5 dB 성능이 향상되었다. 또한 터보 등화기의 반복이 2, 3 회로 늘어남에 따라 약 3.5 dB 성능이 향상되었고, 3회 이상 반복하였을 때는 더 이상 성능이 향상되지 않음을 알 수 있었다.

Torque Ripple Suppression Method for BLDCM Drive Based on Four-Switch Three-Phase Inverter

  • Pan, Lei;Sun, Hexu;Wang, Beibei;Su, Gang;Wang, Xiuli;Peng, Guili
    • Journal of Power Electronics
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    • 제15권4호
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    • pp.974-986
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    • 2015
  • A novel inverter fault-tolerant control scheme is proposed to drive brushless DC motor. A fault-tolerant inverter and its three fault-tolerant schemes (i.e., phase A fault-tolerant, phase B fault-tolerant, and phase C fault-tolerant) are analyzed. Eight voltage vectors are summarized and a voltage vector selection table is used in the control scheme to improve the midpoint current of the split capacitors. A stator flux observer is proposed. The observer can improve flux estimation, which does not require any speed adaptation mechanism and is immune to speed estimation error. Global stability of the flux observer is guaranteed by the Lyapunov stability analysis. A novel stator resistance estimator is incorporated into the sensorless drive to compensate for the effects of stator resistance variation. DC offset effects are mitigated by introducing an integral component in the observer gains. Finally, a control system based on the control scheme is established. Simulation and experiment results show that the method is correct and feasible.

A Study on Bias Effect on Model Selection Criteria in Graphical Lasso

  • Choi, Young-Geun;Jeong, Seyoung;Yu, Donghyeon
    • Quantitative Bio-Science
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    • 제37권2호
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    • pp.133-141
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    • 2018
  • Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

로그형 평균값함수를 고려한 소프트웨어 신뢰성모형에 대한 비교연구 (A Comparative Study of Software Reliability Model Considering Log Type Mean Value Function)

  • 신현철;김희철
    • 디지털산업정보학회논문지
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    • 제10권4호
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    • pp.19-27
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    • 2014
  • Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log type mean value function (Musa-Okumoto and log power model), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing log type mean value function was employed. This analysis of failure data compared with log type mean value function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

열화상 이미지와 환경변수를 이용한 콘크리트 균열 깊이 예측 머신 러닝 분석 (Comparison Analysis of Machine Learning for Concrete Crack Depths Prediction Using Thermal Image and Environmental Parameters)

  • 김지형;장아름;박민재;주영규
    • 한국공간구조학회논문집
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    • 제21권2호
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    • pp.99-110
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    • 2021
  • This study presents the estimation of crack depth by analyzing temperatures extracted from thermal images and environmental parameters such as air temperature, air humidity, illumination. The statistics of all acquired features and the correlation coefficient among thermal images and environmental parameters are presented. The concrete crack depths were predicted by four different machine learning models: Multi-Layer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), and AdaBoost (AB). The machine learning algorithms are validated by the coefficient of determination, accuracy, and Mean Absolute Percentage Error (MAPE). The AB model had a great performance among the four models due to the non-linearity of features and weak learner aggregation with weights on misclassified data. The maximum depth 11 of the base estimator in the AB model is efficient with high performance with 97.6% of accuracy and 0.07% of MAPE. Feature importances, permutation importance, and partial dependence are analyzed in the AB model. The results show that the marginal effect of air humidity, crack depth, and crack temperature in order is higher than that of the others.

A model-based adaptive control method for real-time hybrid simulation

  • Xizhan Ning;Wei Huang;Guoshan Xu;Zhen Wang;Lichang Zheng
    • Smart Structures and Systems
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    • 제31권5호
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    • pp.437-454
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    • 2023
  • Real-time hybrid simulation (RTHS), which has the advantages of a substructure pseudo-dynamic test, is widely used to investigate the rate-dependent mechanical response of structures under earthquake excitation. However, time delay in RTHS can cause inaccurate results and experimental instabilities. Thus, this study proposes a model-based adaptive control strategy using a Kalman filter (KF) to minimize the time delay and improve RTHS stability and accuracy. In this method, the adaptive control strategy consists of three parts-a feedforward controller based on the discrete inverse model of a servohydraulic actuator and physical specimen, a parameter estimator using the KF, and a feedback controller. The KF with the feedforward controller can significantly reduce the variable time delay due to its fast convergence and high sensitivity to the error between the desired displacement and the measured one. The feedback control can remedy the residual time delay and minimize the method's dependence on the inverse model, thereby improving the robustness of the proposed control method. The tracking performance and parametric studies are conducted using the benchmark problem in RTHS. The results reveal that better tracking performance can be obtained, and the KF's initial settings have limited influence on the proposed strategy. Virtual RTHSs are conducted with linear and nonlinear physical substructures, respectively, and the results indicate brilliant tracking performance and superb robustness of the proposed method.

Cosmology with peculiar velocity surveys

  • Qin, Fei
    • 천문학회보
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    • 제46권2호
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    • pp.43.5-44
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    • 2021
  • In the local Universe, the gravitational effects of mass density fluctuations exert perturbations on galaxies' redshifts on top of Hubble's Law, called 'peculiar velocities'. These peculiar velocities provide an excellent way to test the cosmological model in the nearby Universe. In this talk, we present new cosmological constraints using peculiar velocities measured with the 2MASS Tully-Fisher survey (2MTF), 6dFGS peculiar-velocity survey (6dFGSv), the Cosmicflows-3 and Cosmicflows-4TF compilation. Firstly, the dipole and the quadrupole of the peculiar velocity field, commonly named 'bulk flow' and 'shear' respectively, enable us to test whether our cosmological model accurately describes the motion of galaxies in the nearby Universe. We develop and use a new estimators that accurately preserves the error distribution of the measurements to measure these moments. In all cases, our results are consistent with the predictions of the Λ cold dark matter model. Additionally, measurements of the growth rate of structure, fσ8 in the low-redshift Universe allow us to test different gravitational models. We developed a new estimator of the "momentum" (density weighted peculiar velocity) power spectrum and use joint measurements of the galaxy density and momentum power spectra to place new constraints on the growth rate of structure from the combined 2MTF and 6dFGSv data. We recover a constraint of fσ8=0.404+0.082-0.081 at an effective redshift zeff=0.03. This measurement is also fully consistent with the expectations of General Relativity and the Λ Cold Dark Matter cosmological model.

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Adaptive threshold for discrete fourier transform-based channel estimation in generalized frequency division multiplexing system

  • Vincent Vincent;Effrina Yanti Hamid;Al Kautsar Permana
    • ETRI Journal
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    • 제46권3호
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    • pp.392-403
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    • 2024
  • Even though generalized frequency division multiplexing is an alternative waveform method expected to replace the orthogonal frequency division multiplexing in the future, its implementation must alleviate channel effects. Least-squares (LS), a low-complexity channel estimation technique, could be improved by using the discrete Fourier transform (DFT) without increasing complexity. Unlike the usage of the LS method, the DFT-based method requires the receiver to know the channel impulse response (CIR) length, which is unknown. This study introduces a simple, yet effective, CIR length estimator by utilizing LS estimation. As the cyclic prefix (CP) length is commonly set to be longer than the CIR length, it is possible to search through the first samples if CP is larger than a threshold set using the remaining samples. An adaptive scale is also designed to lower the error probability of the estimation, and a simple signal-to-interference-noise ratio estimation is also proposed by utilizing a sparse preamble to support the use of the scale. A software simulation is used to show the ability of the proposed system to estimate the CIR length. Due to shorter CIR length of rural area, the performance is slightly poorer compared to urban environment. Nevertheless, satisfactory performance is shown for both environments.

지수 및 역지수 분포를 이용한 NHPP 소프트웨어 무한고장 신뢰도 모형에 관한 비교연구 (The Comparative Study of NHPP Software Reliability Model Based on Exponential and Inverse Exponential Distribution)

  • 김희철;신현철
    • 한국정보전자통신기술학회논문지
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    • 제9권2호
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    • pp.133-140
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    • 2016
  • 소프트웨어 개발과정에서 소프트웨어 신뢰성은 매우 중요한 이슈이다. 소프트웨어 고장분석을 위한 무한고장 비동질적인 포아송과정에서 고장발생률이 상수이거나, 단조 증가 또는 단조 감소하는 패턴을 가질 수 있다. 본 논문에서는 소프트웨어 신뢰성에 대한 적용 효율을 나타내는 지수 및 역지수분포를 이용한 신뢰성 모형을 비교 제안한다. 효율적인 모형을 위해 평균제곱오차(MSE), 결정계수($R^2$)에 근거한 모델선택, 최우추정법, 이분법에 사용된 파라미터를 평가하기 위한 알고리즘이 적용되였다. 제안하는 지수 및 역지수분포를 이용한 신뢰성 모형를 위해 실제 데이터을 사용한 고장분석이 적용되였다. 고장데이터 분석은 지수 및 역지수분포를 이용한 강도함수와 비교하였다. 데이터 신뢰성을 보장하기 위하여 라플라스 추세검정(Laplace trend test)을 사용하였다. 본 연구에 제안된 역지수분포 신뢰성모형도 신뢰성 측면에서 효율적이기 때문에 (결정계수가 80% 이상) 이 분야에서 기존 모형의 하나의 대안으로 사용할 수 있음을 확인 할 수 있었다. 이 연구를 통하여 소프트웨어 개발자들은 다양한 수명분포를 고려함으로서 소프트웨어 고장형태에 대한 사전지식을 파악하는데 도움을 줄 수 있으리라 사료 된다.

사례기반추론을 이용한 초기단계 공사비 예측 방법: 속성 가중치 산정을 중심으로 (Schematic Cost Estimation Method using Case-Based Reasoning: Focusing on Determining Attribute Weight)

  • 박문서;성기훈;이현수;지세현;김수영
    • 한국건설관리학회논문집
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    • 제11권4호
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    • pp.22-31
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    • 2010
  • 프로젝트 초기단계에서 산정된 공사비는 발주자의 중요한 의사결정에 영향을 미치므로 그 중요성이 강조되고 있지만, 정보의 부족으로 인하여 주로 견적전문가의 경험과 지식에 의존하여 진행된다. 이것은 현재 문제와 가장 유사한 과거 사례를 선택하여 사용하는 사례기반추론으로 발전되었다. 사례기반추론 모델의 예측 성능은 속성 가중치의 산정 결과에 많은 영향을 받으므로, 정확한 속성 가중치의 산정이 요구된다. 기존의 연구는 수학적 방법 또는 전문가의 주관적 판단을 이용하는 방법을 사용한다. 본 연구는 기존 연구의 문제점을 보완하기 위해 유전자 알고리즘을 이용한 사례기반추론 공사비 예측 모델을 제안한다. 공사비 예측 모델은 최근이웃 조회 방법의 과정에 의해 추출한 사례의 공사비 정보를 이용하여 예측 대상의 공사비를 산정한다. 검증 결과 AACE에서 정의한 견적시기별 예측 정확도와 표준화 회귀계수 동일가중치를 사용한 방법보다 높은 오차율을 나타내었다. 따라서 본 연구는 유전자 알고리즘을 도입하여 예측 성능을 향상시키고, 사례기반추론 방법을 사용하여 사용자가 이해하기 용이한 해결책 도출과정을 제시하였다는데 그 의미가 있다.