• Journal of the Korean Statistical Society
• /
• v.22 no.2
• /
• pp.219-234
• /
• 1993

A measuring instrument must be calibrated for accurate inferences of an unknown quantity. Bayesian calibration designs with respect to squared error loss based on a linear model are discussed in Kim and Barlow (1992). In this paper, we consider approximations of the optimal calibration designs using the idea of Gaussian inflence diagrams. The approximation is evaluated by means of numerical calculations, where it is compared with the exact values from the numerical integration.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.215-218
• /
• 1997

A dynamic back-propagation neural network is addressed for adaptive neural control system to approximate non-linear control system rather than static networks. It has the capability to represent the approximation of nonlinear system without mathematical analysis and to carry out the on-line learning algorithm for real time application. The simulated results show fast tracking capability and adaptive response by using dynamic back-propagation neurons.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1823-1827
• /
• 1991

The problem regarding nonlinear systems has come to occupy an important position. In order to solve a nonlinear problem we have methods of linearization which are developed through linear approximation to adapt linear system theories. In this paper we present a formal linearization of nonlinear systems based on the discrete-Fourier transform (D.F.T.).

• Journal of applied mathematics & informatics
• /
• v.34 no.5_6
• /
• pp.421-434
• /
• 2016

The main aim of this paper is to discuss the difference between the Euler-Maruyama's approximate solutions and the accurate solution to stochastic differential delay equation. To make the theory more understandable, we impose the non-uniform Lipschitz condition and weakened linear growth condition. Furthermore, we give the pth moment continuous of the approximate solution for the delay equation.

• Journal of applied mathematics & informatics
• /
• v.9 no.2
• /
• pp.531-542
• /
• 2002

In this paper we deal with a sequence of positive linear operators ${{R_n}}^{[$\beta$]}$ approximating functions on the unbounded interval [0, $\infty$] which were firstly used by K. balazs and J. Szabados. We give pointwise estimates in the framework of polynomial weighted function spaces. Also we establish a Voronovskaja type theorem in the same weighted spaces for ${{K_n}}^{[$\beta$]}$ operators, representing the integral generalization in Kantorovich sense of the ${{R_n}}^{[$\beta$]}$.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10a
• /
• pp.870-875
• /
• 1987

The payload variation and modeling error can lye parameterized in such a way that known nonlinear functions are multiplied linearly by parameter errors. An adaptive control algorithm is derived for a perturbed linear system with such parameterization. Hence, in this approach no linear approximation of robot system is needed for the application of an adaptive law. The stability of the adaptive control algorithm is established and also supported by a computer simulation result.

• Proceedings of the IEEK Conference
• /
• 1999.06a
• /
• pp.691-694
• /
• 1999

This paper presents a performance improvement technique of 2-D towed array shape estimation using Kalman filters. The proposed algorithm by linear model approximation corrects the position errors caused by the Kalman filter results. However, since the assumed linear model makes errors at bending parts, the spline interpolation algorithm based on curve is proposed to reduce the errors.

• Journal of the Korean Statistical Society
• /
• v.21 no.1
• /
• pp.70-79
• /
• 1992

The generalized linear models with random regrssors case are studied for bootstrapping. Only the natural link functions are considered. It is shown that the bootstrap approximation to the distribution of the maximum likelihood estimators is valid for almost all sample sequences. A slight extension of this model is also considered.

• Communications for Statistical Applications and Methods
• /
• v.3 no.1
• /
• pp.235-242
• /
• 1996

When the linear growth birth and death process observed at a set of equidistant time points, McNeil and Weiss (1997) present a method for simultaneously estimating the Malthusian parameter and the sum of the two parameters under wery restricted assumptions using a diffusion approximation. This article suggests a method, which does not require the restrictions given by Weiss, for estimating simultaneously the Malthusian parameter and the sum of the two parameters.

• Journal of applied mathematics & informatics
• /
• v.17 no.1_2_3
• /
• pp.315-328
• /
• 2005

In this paper we present a new method for designing a nozzle. In fact the problem is to find the optimal domain for the solution of a linear or nonlinear boundary value PDE, where the boundary condition is defined over an unspecified domain. By an embedding process, the problem is first transformed to a new shape-measure problem, and then this new problem is replaced by another in which we seek to minimize a linear form over a subset of linear equalities. This minimization is global, and the theory allows us to develop a computational method to find the solution by a finite-dimensional linear programming problem.