• 제목/요약/키워드: optimal error estimates

검색결과 117건 처리시간 0.023초

$L^{\infty}$-CONVERGENCE OF MIXED FINITE ELEMENT METHOD FOR LAPLACIAN OPERATOR

  • Chen, Huan-Zhen;Jiang, Zi-Wen
    • Journal of applied mathematics & informatics
    • /
    • 제7권1호
    • /
    • pp.61-82
    • /
    • 2000
  • In this paper two so-called regularized Green's functions are introduced to derive the optimal maximum norm error estimates for the unknown function and the adjoint vector-valued function for mixed finite element methods of Laplacian operator. One contribution of the paper is a demonstration of how the boundedness of $L^1$-norm estimate for the second Green's function ${\lambda}_2$ and the optimal maximum norm error estimate for the adjoint vector-valued function are proved. These results are seemed to be to be new in the literature of the mixed finite element methods.

STABILITY AND ERROR OF THE VARIABLE TWO-STEP BDF FOR SEMILINEAR PARABOLIC PROBLEMS

  • EMMRICH ETIENNE
    • Journal of applied mathematics & informatics
    • /
    • 제19권1_2호
    • /
    • pp.33-55
    • /
    • 2005
  • The temporal discretisation of a moderate semilinear parabolic problem in an abstract setting by the two-step backward differentiation formula with variable step sizes is analysed. Stability as well as optimal smooth data error estimates are derived if the ratios of adjacent step sizes are bounded from above by 1.91.

FINITE ELEMENT APPROXIMATIONS OF THE OPTIMAL CONTROL PROBLEMS FOR STOCHASTIC STOKES EQUATIONS

  • Choi, Youngmi;Kim, Soohyun;Lee, Hyung-Chun
    • 대한수학회보
    • /
    • 제51권3호
    • /
    • pp.847-862
    • /
    • 2014
  • Finite element approximation solutions of the optimal control problems for stochastic Stokes equations with the forcing term perturbed by white noise are considered. Error estimates are established for the fully coupled optimality system using Brezzi-Rappaz-Raviart theory. Numerical examples are also presented to examine our theoretical results.

면적강우량 산정을 위한 관측망 최적설계 연구 (Optimal Network Design for the Estimation of Areal Rainfall)

  • 이재형;유양규
    • 한국수자원학회논문집
    • /
    • 제35권2호
    • /
    • pp.187-194
    • /
    • 2002
  • 하천유역 면적강우량 산정의 정확도를 개선하기 위하여 기존 강우관측자료의 통계적 특성을 이용한 강우관측망의 최적설계방법을 연구하였다. 최적설계를 위한 목적함수는 면적강우량의 추정오차 및 지점강우량 관측비용의 항으로 구성하고, 그 값이 최소인 관측망은 선정하였다. 통계f7파의 추정방법으로는 통계적 분산 산정방법인 크리깅 모형을 채택하였다. 비용은 강우관측소의 설치비와 연간운영 비론 적용하고, 오차항과 비용항의 통합에는 등치매개변수를 이용하였다. 연구된 최적설계방법을 댐 신설로 강우관측소 증설이 필요한 용담댐 유역에 적용하여, 대상유역의 최적 강우관측망을 제안하였다.

Optimum Superimposed Training for Mobile OFDM Systems

  • Yang, Qinghai;Kwak, Kyung-Sup
    • Journal of Communications and Networks
    • /
    • 제11권1호
    • /
    • pp.42-46
    • /
    • 2009
  • Superimposed training (SIT) design for estimating of time-varying multipath channels is investigated for mobile orthogonal frequency division multiplexing (OFDM) systems. The design of optimum SIT consists of two parts: The optimal SIT sequence is derived by minimizing the channel estimates' mean square error (MSE); the optimal power allocation between training and information data is developed by maximizing the averaged signal to interference plus noise ratio (SINR) under the condition of equal powered paths. The theoretical analysis is verified by simulations. For the metric of the averaged SINR against signal to noise ratio (SNR), the theoretical result matches the simulation result perfectly. In contrast to an interpolated frequency-multiplexing training (FMT) scheme or an SIT scheme with random pilot sequence, the SIT scheme with proposed optimal sequence achieves higher SINR. The analytical solution of the optimal power allocation is demonstrated by the simulation as well.

이산 비선형 시스템에 대한 유한 임펄스 응답 고정 시간 지연 평활기 (A Finite Impulse Response Fixed-lag Smoother for Discrete-time Nonlinear Systems)

  • 권보규;한세경;한수희
    • 제어로봇시스템학회논문지
    • /
    • 제21권9호
    • /
    • pp.807-810
    • /
    • 2015
  • In this paper, a finite impulse response(FIR) fixed-lag smoother is proposed for discrete-time nonlinear systems. If the actual state trajectory is sufficiently close to the nominal state trajectory, the nonlinear system model can be divided into two parts: The error-state model and the nominal model. The error state can be estimated by adapting the optimal time-varying FIR smoother to the error-state model, and the nominal state can be obtained directly from the nominal trajectory model. Moreover, in order to obtain more robust estimates, the linearization errors are considered as a linear function of the estimation errors. Since the proposed estimator has an FIR structure, the proposed smoother can be expected to have better estimation performance than the IIR-structured estimators in terms of robustness and fast convergence. Additionally the proposed method can give a more general solution than the optimal FIR filtering approach, since the optimal FIR smoother is reduced to the optimal FIR filter by setting the fixed-lag size as zero. To illustrate the performance of the proposed method, simulation results are presented by comparing the method with an optimal FIR filtering approach and linearized Kalman filter.

$L^1$ Bandwidth Selection in Kernel Regression Function Estimation

  • Jhun, Myong-Shic
    • Journal of the Korean Statistical Society
    • /
    • 제17권1호
    • /
    • pp.1-8
    • /
    • 1988
  • Kernel estimates of an unknown regression function are studied. Bandwidth selection rule minimizing integrated absolute error loss function is considered. Under some reasonable assumptions, it is shown that the optimal bandwidth is unique and can be computed by using bisection algorithm. Adaptive bandwidth selection rule is proposed.

  • PDF

Basic Study of the Optimization of the Gain Parameters α, β and γ of a Tracking Module for ARPA system on Board High Dynamic Warships

  • Pan, Bao-Feng;Njonjo, Anne Wanjiru;Jeong, Tae-Gweon
    • 한국항해항만학회:학술대회논문집
    • /
    • 한국항해항만학회 2016년도 춘계학술대회
    • /
    • pp.305-307
    • /
    • 2016
  • The purpose of this paper is to determine the optimal values of the gain parameters used in the tracking module for a highly dynamic warship. The algorithm of the tracking module uses the ${\alpha}-{\beta}-{\gamma}$ filter to compute accurate estimates and update the state variables, that is, positions, velocity and acceleration. The filtering coefficients ${\alpha}$, ${\beta}$ and ${\gamma}$ are determined from set values of the damping parameter, ${\xi}$. Optimization is achieved by plotting a range of the damping parameter ${\xi}$ against the corresponding residual error and then selecting the best value of ${\xi}$ with the minimum residual error. Optimal values of the smoothing coefficients are subsequently computed from the selected damping parameter, ${\xi}$.

  • PDF

OPTIMAL ERROR ESTIMATE OF A DECOUPLED CONSERVATIVE LOCAL DISCONTINUOUS GALERKIN METHOD FOR THE KLEIN-GORDON-SCHRÖDINGER EQUATIONS

  • YANG, HE
    • Journal of the Korean Society for Industrial and Applied Mathematics
    • /
    • 제24권1호
    • /
    • pp.39-78
    • /
    • 2020
  • In this paper, we propose a decoupled local discontinuous Galerkin method for solving the Klein-Gordon-Schrödinger (KGS) equations. The KGS equations is a model of the Yukawa interaction of complex scalar nucleons and real scalar mesons. The advantage of our scheme is that the computation of the nucleon and meson field is fully decoupled, so that it is especially suitable for parallel computing. We present the conservation property of our fully discrete scheme, including the energy and Hamiltonian conservation, and establish the optimal error estimate.