• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.7 no.2
• /
• pp.1-5
• /
• 2013

In this paper, we proposed how to estimate the walking state in the knee disarticulation prosthesis's knee angle control. In control of the knee disarticulation prosthesis, we can estimate walking state that measurement of knee angle using absolute encoder and measurement of load on the soles using strain gage. We suggested a method of estimating the current walking states which can be divided into four cases and showed the effectiveness of the method via a series of experiments.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.20 no.4
• /
• pp.7-13
• /
• 2012

This paper is to estimate aerodynamic coefficients needed to determine the missiles' controller design and stability from simulation data of Skid-to-Turn missile. Method of determining aerodynamic coefficients is to apply Neural Network and Recursive Least Square and results were compared and researched. Also analysing actual flight test data was considered and sensor noise was added. Estimate parameter of data with sensor noise added and estimated performance and reliability for both methods that did not need initial values. Both Neural Network and Recursive Least Square methods showed excellent estimate results without adding the noise and with noise added Neural Network method showed better estimate results.

• Journal of Mechanical Science and Technology
• /
• v.16 no.11
• /
• pp.1379-1394
• /
• 2002

In case of a single input single output (SISO) system with a nonlinear term, a signal compression method is useful to identify a system because the equivalent impulse response of linear part from the system can be extracted by the method. However even though the signal compression method is useful to estimate uncertain parameters of the system, the method cannot be directly applied to a unique system with hysteresis characteristics because it cannot estimate all of the two different dynamic properties according to its motion direction. This paper proposes a signal compression method with a pre-processor to identify a unique system with two different dynamics according to its motion direction. The pre-processor plays a role of separating expansion and retraction properties from the system with hysteresis characteristics. For evaluating performance of the proposed approach, a simulation to estimate the assumed unknown parameters for an arbitrary known model is carried out. A motion platform with several single-rod cylinders is a representative unique system with two different dynamics, because each single-rod cylinder has expansion and retraction dynamic properties according to its motion direction. The nominal constant parameters of the motion platform are experimentally identified by using the proposed method. As its application, the identified parameters are applied to a design of a sliding mode controller for the simulator.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.9 no.4
• /
• pp.337-342
• /
• 2016

In this paper, we studied a modified linear prediction method to estimate target signal correctly. Linear prediction method estimate direction-of-arrival to linear combination for any antenna element and other antenna elements. Modified linear prediction used optimal weight and posterior probability method. Through simulation, we are comparative analysis about the performance of proposed, bartlett and MUSIC method. From simulation, Bartlett and MUSIC method was estimation 3 targets signal, and proposed method estimated 4 targets. We showed the superior performance of the proposed algorithm relative to the classical method in order to estimate of target signals.

• The Journal of Korea Robotics Society
• /
• v.3 no.3
• /
• pp.176-185
• /
• 2008

In this paper, new filtering method for sensor registration is provided to estimate and correct error of registration parameters in multiple sensor environments. Sensor registration is based on filtering method to estimate registration parameters in multiple sensor environments. Accuracy of sensor registration can increase performance of data fusion method selected. Due to various error sources, the sensor registration has registration errors recognized as multiple objects even though multiple sensors are tracking one object. In order to estimate the error parameter, new nonlinear information filtering method is developed using minimum mean square error estimation. Instead of linearization of nonlinear function like an extended Kalman filter, information estimation through unscented prediction is used. The proposed method enables to reduce estimation error without a computation of the Jacobian matrix in case that measurement dimension is large. A computer simulation is carried out to evaluate the proposed filtering method with an extended Kalman filter.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2216-2218
• /
• 2002

A system identification is to measure the output in the presence of a adequate input for the controlled system and to estimate the mathematical model in the basic of input output data. In the system identification, it is possible to estimate the true parameter values by the adjusted least squares method in the input-output case of no observed noise, and it is possible to estimate the true parameter values by the total least squares method in the input-output case with the observed noise. In recent the adjusted least squares method is suggested as a consistent estimation method in the system identification not with the observed noise input but with the observed noise output. In this paper we have developed the adjusted least squares method from the least squares method and have made certain of the efficiency in comparing the estimating results with the generating data by the computer simulations.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1730-1733
• /
• 1991

In this paper, we two dimensional processing method is presented, which can accurately determine the orientation of an part. Matching bewteen the object and the object contour is decomposed to estimate the orientation of the object and to evaluate the similarity new approach is very robust with respect to noise and no preprocessing of the contour is required. Also, this method has many advantages over the converntional correlation technique. With only a few uniformly sampled points, this method can estimate the accurate orientation in an efficient manner even in a noisy environment.

• Communications of the Korean Mathematical Society
• /
• v.34 no.3
• /
• pp.1015-1027
• /
• 2019

A class of systems of singularly perturbed convection diffusion type equations with integral boundary conditions is considered. A numerical method based on a finite difference scheme on a Shishkin mesh is presented. The suggested method is of almost first order convergence. An error estimate is derived in the discrete maximum norm. Numerical examples are presented to validate the theoretical estimates.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.12
• /
• pp.3009-3015
• /
• 2013

Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer and method of the most fundamental being determining an individual's genotype from multiple aligned short read sequences at a position. Bayesian algorithm estimate parameter using posterior genotype probabilities and other method, EM algorithm, estimate parameter using maximum likelihood estimate method in observed data. Here, we propose a novel genotype-calling system and compare and analyze the effect of sample size(S = 50, 100 and 500) on posterior estimate of sequencing error rate, somatic mutation status and genotype probability. The result is that estimate applying Bayesian algorithm even for 50 of small sample size approached real parameter than estimate applying EM algorithm in small sample more accurately.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2002.03a
• /
• pp.297-305
• /
• 2002

As advanced earthquake analysis/design methods such as the nonlinear static analysis are developed, it is required to estimate precisely the cyclic behavior of reinforced concrete members that is characterized by strength, deformability, and capacity of energy dissipation. However, currently, estimation of energy dissipation depends on empirical equations that are not sufficiently accurate, or experiment and sophisticated numerical analysis which are difficult to use in practice. In the present study, nonlinear finite element analysis was performed to investigate the behavioral characteristics of flexure-dominant RC members under cyclic load. The effects of axial force, arrangement of reinforcing bars, and reinforcement ratio on the cyclic behavior were studied. Based on the investigation, a simplified method to estimate the capacity of energy dissipation was proposed, and it was verified by the comparison with the finite element analyses and experiments. The proposed method can estimate the energy dissipation of RC members more precisely than currently used empirical equations, and it is easily applicable in practice.