• Title/Summary/Keyword: computer based estimation

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Control of mobile robots based on a linear optic-flow algorithm (선형 Optic flow 알고리듬을 이용한 이동 로봇 제어)

  • 최대일;한웅기;국태용
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1149-1152
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    • 1996
  • Recently visual servo control is an important feature of an intelligent robot system. In this paper, we presents a Kalman filter approach for estimation of the linear optic flow model which is utilized in the visual servoing of a mobile robot. The proposed method is also compared with the conventional least mean square method via computer simulation.

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A Study on Adaptive Mesh Generation for the Finite Element Method using h-Method (h-법에 의한 순응형 유한요소 재분할에 관한 연구)

  • 장창두;김병일
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1992.04a
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    • pp.39-44
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    • 1992
  • This paper proposes a method of h-type adaptive mesh generation for the finite element analysis of two dimensional elasticity problem. The error energy norm of a posteriori error estimation is difined based on the complementary energy of each element. Computer codes are developed and some examples are investigated. It is shown that the approach to the optimized mesh in this paper is effective and useful.

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Reliability Estimation in Bivariate Pareto Model with Bivariate Type I Censored Data

  • Cho, Jang-Sik;Cho, Kil-Ho;Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.837-844
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    • 2003
  • In this paper, we obtain the estimator of system reliability for the bivariate Pareto model with bivariate type 1 censored data. We obtain the estimators and approximated confidence intervals of the reliability for the parallel system based on likelihood function and the relative frequency, respectively. Also we present a numerical example by giving a data set which is generated by computer.

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Object matching algorithms using robust hausdorff distance measure (Robust hausdorff 거리 척도를 이용한 물체 정합 알고리듬)

  • 권오규;심동규;박래홍
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.11
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    • pp.93-101
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    • 1997
  • A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper proposes three object matching algorithm using robust HD measures based on M-estimation, least trimmed square (LTS), and .alpha.-trimmed mean methods, which are more efficient than the conventional HD measures. By computer simulation with synthetic and real images, the matching performance of the conventional HD smeasures and proposed' robust ones is compared.

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Bayesian reliability estimation in a stress-strength system

  • Chang, In-Hong;Oh, Soo-Jin
    • Journal of Applied Reliability
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    • v.11 no.2
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    • pp.151-165
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    • 2011
  • We consider the problem of estimating the system reliability using noninformative priors when both stress and strength follow generalized gamma distributions with index, scale, and shape parameters. We first derive group-ordering reference priors using the reparametrization. We next provide the sufficient condition for propriety of posterior distributions and provide marginal posterior distributions under those noninformative priors. Finally, we provide and compare estimated values of the system reliability based on the simulated values of parameter of interest in some special cases.

Optimization of sensor location for source localization : Minimum-Norm Least-Square Method (신호원 국소화를 위한 위치의 최적화 : MNLS)

  • 김유정;한주만;이인범;박광석
    • Proceedings of the IEEK Conference
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    • 2000.06e
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    • pp.124-126
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    • 2000
  • The Minimum-Norm Least-Square(MNLS) approach based on lead field theory is an useful method to find an unique inverse solution for the measured magnetic field. The lead field depends on head geometry and location of sources and sensors. So, optimization of sensor array location is important issue for MNLS estimation. In this paper, we present an investigation for the optimization of sensor array location in computer simulation.

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Basic Aspects of Signal Processing in Ultrasonic Imaging

  • Saito, Masao
    • Journal of Biomedical Engineering Research
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    • v.5 no.1
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    • pp.5-8
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    • 1984
  • As the ensemble averaged dz/dt signal during exercise gets smoothed, it is difficult to find the distinctive marks for estimation of stroke volume. The cross correlation function was made use of estmating these marks for automatic calculation by computer from the ensemble averaged dz/dt signal. LVET(Left Ventricular Ejection Time) and stroke volume were estimated based on the calculated parameters from the characteristic points. LVET, stroke volume calculated by hand, by the ensemble average and the cross correlation were compared for accuracy validation.

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Detection of Distinctive Points in Impedance Cardiogram during Exercise by Cross-Correlation Method (상호상관 관계를 이용한 운동중의 임피던스 파형에서의 특성점 검출)

  • 오인식;송철규
    • Journal of Biomedical Engineering Research
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    • v.12 no.4
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    • pp.261-266
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    • 1991
  • As the ensemble averaged dz/dt signal during exercise gets smoothed, it is difficult to find the distinctive marks for estimation of stroke volume. The cross correlation function was made use of estimating these marks for automatic calculation by computer from the ensemble averaged dz/dt signal. LVET( Left Ventricular Ejection Time) and stroke volume were estimated based on the calculated parameters from the characteristic points. LVET, stroke volume calculated by hand, by the ensemble average and the cross correlation were compared for accuracy validation.

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Distance Measurement Using the Kinect Sensor with Neuro-image Processing

  • Sharma, Kajal
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.6
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    • pp.379-383
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    • 2015
  • This paper presents an approach to detect object distance with the use of the recently developed low-cost Kinect sensor. The technique is based on Kinect color depth-image processing and can be used to design various computer-vision applications, such as object recognition, video surveillance, and autonomous path finding. The proposed technique uses keypoint feature detection in the Kinect depth image and advantages of depth pixels to directly obtain the feature distance in the depth images. This highly reduces the computational overhead and obtains the pixel distance in the Kinect captured images.