• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.4
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• pp.55-68
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• 2007

First-order least-squares method of a distributed optimal control problem for the incompressible Navier-Stokes equations is considered. An optimality system for the optimal solution are reformulated to the equivalent first-order system by introducing velocity-flux variables and then the least-squares functional corresponding to the system is defined in terms of the sum of the squared $L^2$ norm of the residual equations of the system. The optimal error estimates for least-squares finite element approximations are obtained.

• Progress in Superconductivity
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• v.7 no.1
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• pp.36-40
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• 2005

The problem of fluctuation-induced digital errors in a rapid single flux quantum (RSFQ) circuit has been a very important issue. In this work, we calculated the bit error rate of an RSFQ switch used in superconductive arithmetic logic unit (ALU). RSFQ switch should have a very low error rate in the optimal bias. Theoretical estimates of the RSFQ error rate are on the order of $10^{-50}$ per bit operation. In this experiment, we prepared two identical circuits placed in parallel. Each circuit was composed of 10 Josephson transmission lines (JTLs) connected in series with an RSFQ switch placed in the middle of the 10 JTLs. We used a splitter to feed the same input signal to both circuits. The outputs of the two circuits were compared with an RSFQ exclusive OR (XOR) to measure the bit error rate of the RSFQ switch. By using a computerized bit-error-rate test setup, we measured the bit error rate of $2.18{\times}10^{-12}$ when the bias to the RSFQ switch was 0.398 mA that was quite off from the optimum bias of 0.6 mA.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.507-518
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• 2017

Volatility plays a crucial role in theory and applications of asset pricing, optimal portfolio allocation, and risk management. This paper proposes a combined model of autoregressive moving average (ARFIMA), generalized autoregressive conditional heteroscedasticity (GRACH), and skewed-t error distribution to accommodate important features of volatility data; long memory, heteroscedasticity, and asymmetric error distribution. A fully Bayesian approach is proposed to estimate the parameters of the model simultaneously, which yields parameter estimates satisfying necessary constraints in the model. The approach can be easily implemented using a free and user-friendly software JAGS to generate Markov chain Monte Carlo samples from the joint posterior distribution of the parameters. The method is illustrated by using a daily volatility index from Chicago Board Options Exchange (CBOE). JAGS codes for model specification is provided in the Appendix.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.52-61
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• 1993

This paper deals with adaptive control method of a robot manipulator with one-flexible link. ARMA model is used as a prediction and estimation model, and adaptive control scheme consists of parameter estimation part and adaptive controller. Parameter estimation part estimates ARMA model's coefficients by using recursive least-squares(RLS) algorithm and generates the predicted output. Variable forgetting factor (VFF) is introduced to achieve an efficient estimation, and adaptive controller consists of reference model, error dynamics model and minimum prediction error controller. An optimal input is obtained by minimizing input torque, it's successive input change and the error between the predicted output and the reference output.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.13 no.3
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• pp.169-180
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• 2009

A discontinuous Galerkin method with interior penalty terms is presented for linear Sobolev equation. On appropriate finite element spaces, we apply a symmetric interior penalty Galerkin method to formulate semidiscrete approximate solutions. To deal with a damping term $\nabla{\cdot}({\nabla}u_t)$ included in Sobolev equations, which is the distinct character compared to parabolic differential equations, we choose special test functions. A priori error estimate for the semidiscrete time scheme is analyzed and an optimal $L^\infty(L^2)$ error estimation is derived.

• Journal of the Korean Mathematical Society
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• v.39 no.3
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• pp.363-376
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• 2002

Stability result is obtained for the approximation of the stationary Stokes problem with nonconforming elements proposed by Douglas et al [1] for the velocity and discontinuous piecewise constants for the pressure on qudrilateral elements. Optimal order $H^1$and $L^2$error estimates are derived.

• Bulletin of the Korean Mathematical Society
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• v.51 no.6
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• pp.1655-1668
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• 2014

In this article, we propose and analyze a new nonconforming primal mixed finite element method for the stationary Stokes equations. The approximation is based on the pseudostress-velocity formulation. The incompressibility condition is used to eliminate the pressure variable in terms of trace-free pseudostress. The pressure is then computed from a simple post-processing technique. Unique solvability and optimal convergence are proved. Numerical examples are given to illustrate the performance of the method.

• ETRI Journal
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• v.28 no.6
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• pp.822-825
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• 2006

Based on superimposed training methods, a novel time-varying multipath channel estimation scheme is proposed for orthogonal frequency division multiplexing systems. We first develop a linear least square channel estimator, and meanwhile find the optimal superimposed sequences with respect to the channel estimates' mean square error. Next, a low-rank approximated channel estimator is obtained by using the singular value decomposition. As demonstrated in simulations, the proposed scheme achieves not only better performance but also higher bandwidth efficiency than the conventional pilot-aided approach.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.251-264
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• 2004

We introduce a semidiscrete mixed finite element approximation for the single-phase linear Stefan problem and show the unique existence of the approximation. And the optimal rate of convergence in $L^2$ and $H^1$ norms are derived.

• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.795-809
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• 2001

In this paper, we apply finite element Galerkin method to a single-ohase linear Stefan problem with a forcing term. We apply the extrapolated Crank-Nicolson method to construct the fully discrete approximation and we derive optimal error estimates in the temporal direction in $L^2$, $H^1$ spaces.