• 제목/요약/키워드: covariance model

검색결과 640건 처리시간 0.02초

간접 되먹임 필터를 이용한 관성센서 및 초음파 속도센서 기반의 수중 복합항법 알고리듬 (Underwater Hybrid Navigation Algorithm Based on an Inertial Sensor and a Doppler Velocity Log Using an Indirect Feedback Kalman Filter)

  • 이종무;이판묵;성우제
    • 한국해양공학회지
    • /
    • 제17권6호
    • /
    • pp.83-90
    • /
    • 2003
  • This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), and a Doppler velocity log (DVL), accompanied by a magnetic compass. The errors of inertial measurement units increase with time, due to the bias errors of gyros and accelerometers. A navigational system model is derived, to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 20. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors, and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o,f equations of motion of SAUV, using a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance, by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass, and a depth sensor. The error of the estimated position still slowly drifts in the horizontal plane, about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

공분산분석에서 선형위치통계량을 이용한 비모수 검정법 (Nonparametric method using linear statistics in analysis of covariance model)

  • 최윤정;김동재
    • 응용통계연구
    • /
    • 제30권3호
    • /
    • pp.427-439
    • /
    • 2017
  • 공변량(covariate)이 존재하는 경우, 각 처리군 간 효과의 차이를 검정하기 위한 대표적인 비모수적 방법에는 Quade (1967)가 제안한 검정법이 있다. 또한 반응변수에 대해 공변량으로 단순선형회귀분석을 실시하여 얻은 잔차에 대해 일원배치분산분석과 Kruskal Wallis가 제안한 방법을 적용하는 방법, 그리고 Hwang과 Kim (2012)이 제안한 비모수적 도구인 위치(placement)를 이용한 방법이 있다. 본 논문에서는 공분산분석 모형에서 Hwang과 Kim (2012)이 제안한 방법을 확장하여 공분산분석에서의 새로운 방법을 제안하였다. 또한 모의실험(Monte Carlo simulation study)을 통하여 기존의 검정법들과 제안한 방법의 검정력을 비교하였다.

효모 마이크로어레이 유전자 발현데이터에 대한 가우시안 과정 회귀를 이용한 유전자 선별 및 군집화 (Screening and Clustering for Time-course Yeast Microarray Gene Expression Data using Gaussian Process Regression)

  • 김재희;김태훈
    • 응용통계연구
    • /
    • 제26권3호
    • /
    • pp.389-399
    • /
    • 2013
  • 본 연구에서는 가우시안 과정회귀방법을 소개하고 시계열 마이크로어레이 유전자 발현데이터에 대해 가우시안 과정회귀를 적용한 사례를 보이고자한다. 가우시안 과정회귀를 적합하여 로그 주변우도함수 비를 이용한 유전자를 선별방법에 대한 모의실험을 통해 민감도, 특이도, 위발견율 등을 계산하여 선별방법으로의 활용성을 보였다. 실제 효모세포주기 데이터에 대해 제곱지수공분산함수를 고려한 가우시안 과정회귀를 적합하여 로그 주변우도함수 비를 이용하여 차변화된 유전자를 선별한 후, 선별된 유전자들에 대해 가우시안 모형기반 군집화를 하고 실루엣 값으로 군집유효성을 보였다.

Time-history analysis based optimal design of space trusses: the CMA evolution strategy approach using GRNN and WA

  • Kaveh, A.;Fahimi-Farzam, M.;Kalateh-Ahani, M.
    • Structural Engineering and Mechanics
    • /
    • 제44권3호
    • /
    • pp.379-403
    • /
    • 2012
  • In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

IIR(SPKF)/FIR(MRHKF 필터) 융합 필터 및 성능 분석 (IIR(SPKF)/FIR(MRHKF Filter) Fusion Filter and Its Performance Analysis)

  • 조성윤
    • 제어로봇시스템학회논문지
    • /
    • 제13권12호
    • /
    • pp.1230-1242
    • /
    • 2007
  • This paper describes an IIR/FIR fusion filter for a nonlinear system, and analyzes the stability of the fusion filter. The fusion filter is applied to INS/GPS integrated system, and the performance is verified by simulation and experiment. In the fusion filter, an IIR-type filter (SPKF) and FIR-type filter (MRHKF filter) are processed independently, then the two filters are merged using the mixing probability calculated using the residuals and residual covariance information of the two filters. The merits of the SPKF and the MRHKF filter are embossed and the demerits of the filters are diminished via the filter fusion. Consequently, the proposed fusion filter has robustness against to model uncertainty, temporary disturbing noise, large initial estimation error, etc. The stability of the fusion filter is verified by showing the closeness of the states of the two sub filters in the mixing/redistribution process and the upper bound of the error covariance matrices. This fusion filter is applied into INS/GPS integrated system, and important factors for filter processing are presented. The performance of the INS/GPS integrated system designed using the fusion filter is verified by simulation under various error environments and is confirmed by experiment.

Comparing Learning Outcome of e-Learning with Face-to-Face Lecture of a Food Processing Technology Course in Korean Agricultural High School

  • PARK, Sung Youl;LEE, Hyeon-ah
    • Educational Technology International
    • /
    • 제8권2호
    • /
    • pp.53-71
    • /
    • 2007
  • This study identified the effectiveness of e-learning by comparing learning outcome in conventional face-to-face lecture with the selected e-learning methods. Two e-learning contents (animation based and video based) were developed based on the rapid prototyping model and loaded onto the learning management system (LMS), which is http://www.enaged.co.kr. Fifty-four Korean agricultural high school students were randomly assigned into three groups (face-to-face lecture, animation based e-learning, and video based e-learning group). The students of the e-learning group logged on the LMS in school computer lab and completed each e-learning. All students were required to take a pretest and posttest before and after learning under the direction of the subject teacher. A one-way analysis of covariance was administered to verify whether there was any difference between face-to-face lecture and e-learning in terms of students' learning outcomes after controlling the covariate variable, pretest score. According to the results, no differences between animation based and video based e-learning as well as between face-to-face learning and e-learning were identified. Findings suggest that the use of well designed e-learning could be worthy even in agricultural education, which stresses hands-on experience and lab activities if e-learning was used appropriately in combination with conventional learning. Further research is also suggested, focusing on a preference of e-learning content type and its relationship with learning outcome.

Bootstrap confidence intervals for classification error rate in circular models when a block of observations is missing

  • Chung, Hie-Choon;Han, Chien-Pai
    • Journal of the Korean Data and Information Science Society
    • /
    • 제20권4호
    • /
    • pp.757-764
    • /
    • 2009
  • In discriminant analysis, we consider a special pattern which contains a block of missing observations. We assume that the two populations are equally likely and the costs of misclassification are equal. In this situation, we consider the bootstrap confidence intervals of the error rate in the circular models when the covariance matrices are equal and not equal.

  • PDF

An Alternative Proof of the Asymptotic Behavior of GLSE in Polynomial MEM

  • Myung-Sang Moon
    • Communications for Statistical Applications and Methods
    • /
    • 제3권3호
    • /
    • pp.75-81
    • /
    • 1996
  • Polynomial measurement error model(MEM) with one predictor is considered. It is briefly mentioned that Chan and Mak's generalized least squares estimator(GLSE) can be derived more easily if Hermite polynomial concept is applied. It is proved that GLSE derived using new procedure is equivalent to the estimator obtained from corrected score function. Finally, much simpler proof of the asymptotic behavior of GLSE than that of Chan and Mak is provided. Much simpler formula of asymptotic covariance matrix of GLSE is a part of that proof.

  • PDF

Estimating Parameters in Muitivariate Normal Mixtures

  • Ahn, Sung-Mahn;Baik, Sung-Wook
    • Communications for Statistical Applications and Methods
    • /
    • 제18권3호
    • /
    • pp.357-365
    • /
    • 2011
  • This paper investigates a penalized likelihood method for estimating the parameter of normal mixtures in multivariate settings with full covariance matrices. The proposed model estimates the number of components through the addition of a penalty term to the usual likelihood function and the construction of a penalized likelihood function. We prove the consistency of the estimator and present the simulation results on the multi-dimensional nor-mal mixtures up to the 8-dimension.

시공간 베이지안 계층모형-미국 연기온 편차자료에 적용-

  • 이의규;문명상
    • 한국통계학회:학술대회논문집
    • /
    • 한국통계학회 2002년도 추계 학술발표회 논문집
    • /
    • pp.163-168
    • /
    • 2002
  • 전형적인 시공간모형은 시공간 변이도(semivariogram) 또는 공분산 함수(covariance function)를 필요로 한다. 본 논문에서는 계산하기 어렵고 현실적이지 못한 결합 공분산함수를 통한 고전적 모형 대신, 일련의 독립적인 조건분포를 이용하는 보다 현실적인 베이지안 계층모형을 이용한다. 미국 전 지역에 산재해 있는 138개 기온 관측소로부터 얻어진 61년(1920-1980) 동안의 연기온편차 자료에 시공간 베이지안 계층모형을 적용하고 순수시계열모형에서의 적합값과 제안된 모형의 적합값을 비교분석한다.

  • PDF