• Communications for Statistical Applications and Methods
• /
• v.6 no.1
• /
• pp.169-180
• /
• 1999

A Markov Chain Monte Carlo method with development of computation is used to be the software system reliability probability model. For Bayesian estimator considering computational problem and theoretical justification we studies relation Markov Chain with Gibbs sampling. Special case of GOS with Superposition for Goel-Okumoto and Weibull models using Gibbs sampling and Metropolis algorithm considered. In this paper discuss Bayesian computation and model selection using posterior predictive likelihood criterion. We consider in this paper data using method by Cox-Lewis. A numerical example with a simulated data set is given.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.91.4-91
• /
• 2001

In this paper, a development of the sensor fusion algorithm for a visual control of mobile robot is presented. The output data from the visual sensor include a time-lag due to the image processing computation. The sampling rate of the visual sensor is considerably low so that it should be used with other sensors to control fast motion. The main purpose of this paper is to develop a method which constitutes a sensor fusion system to give the optimal state estimates. The proposed sensor fusion system combines the visual sensor and inertial sensor using a modified Kalman filter. A kind of multi-rate Kalman filter which treats the slow sampling rate ...

• Journal of the Korean Statistical Society
• /
• v.31 no.4
• /
• pp.509-518
• /
• 2002

This paper is concerned with semiparametric Bayesian analysis of the proportional intensity regression model of the Poisson process for multiple event time data. A nonparametric prior distribution is put on the baseline cumulative intensity function and a usual parametric prior distribution is given to the regression parameter. Also we allow heterogeneity among the intensity processes in different subjects by using unobserved random frailty components. Gibbs sampling approach with the Metropolis-Hastings algorithm is used to explore the posterior distributions. Finally, the results are applied to a real data set.

• Communications for Statistical Applications and Methods
• /
• v.20 no.6
• /
• pp.427-438
• /
• 2013

Based on progressive Type II censored sampling which is an important method to obtain failure data in a lifetime study, we suggest a very general form of Bayesian prediction bounds from two parameters exponentiated Weibull distribution using the proper general prior density. For this, Markov chain Monte Carlo approach is considered and we also provide a simulation study.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.7
• /
• pp.898-902
• /
• 2018

A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

• The Korean Journal of Applied Statistics
• /
• v.13 no.2
• /
• pp.415-425
• /
• 2000

We proposed a new classification algorithm based on bootstrap sampling and pairwise coupling method. Also, for comparing the accuracy of a proposed algorithm with those of old methods, we conducted classification with waveform data and others.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1348-1351
• /
• 1996

In field bus network, field device are connected with a medium. Because a medium must be shared for transmitting data, there are random delay time when data arrive destination station. It is difficult that all data packets are guaranteed synchronization and real-time restriction. In this paper, we show an algorithm that makes network utilization to maximum, guarantees real-time restriction, calculates sampling time at all control loop.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.244-247
• /
• 1986

A revised two-level costate prediction algorithm is developed for the optimization of nonlinear nuclear power plant. The algorithm is proved to converge very well, and appears to require substantially small computation time and storage than previous nonlinear optimization algorithm. To cope with unknown external disturbances, we construct a closed loop control system. In order to get a smaller sampling time, this paper proposes the two-level Kalman filter.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.298-303
• /
• 1986

A robust and efficient dynamic control algorithm for the position control of robotic manipulators is proposed. This algorithm consists of an open loop control and a closed loop control. The former may have a larger sampling time than the latter. The robustness and efficiency of this algorithm is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.

• Journal of Biomedical Engineering Research
• /
• v.5 no.1
• /
• pp.25-32
• /
• 1984

In this paper a new "limited view frequency correlation algorithm" for diffraction topography is proposed. In this algorithm the problem of limited view sampling is solved by spectrum of spatial frequencies of refractive index. This algorithm is very important in a view of reduction of scanning time and improvement of considerably higher image quality object reconstruction.struction.