• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제25권4호
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• pp.224-261
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• 2021

The interest in implicit-explicit (IMEX) integration methods has emerged as an alternative for dealing in a computationally cost-effective way with stiff ordinary differential equations arising from practical modeling problems. In this paper, we introduce implicit-explicit second derivative linear multi-step methods (IMEX SDLMM) with error control. The proposed IMEX SDLMM is based on second derivative backward differentiation formulas (SDBDF) and recursive SDBDF. The IMEX second derivative schemes are constructed with order p ranging from p = 1 to 8. The methods are numerically validated on well-known stiff equations.

• 전력전자학회논문지
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• 제24권4호
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• pp.286-293
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• 2019

This study compares and analyzes online update techniques, which estimate the parameters of battery equivalent circuit models in real time. Online update techniques, which are based on extended Kalman filter and recursive least square methods, are constructed by considering the dynamic characteristics of batteries. The performance of the online update techniques is verified by simulation and experiments. Each online update technique is compared and analyzed in terms of complexity and accuracy to propose a suitable guide for selecting algorithms on various types of battery applications.

• 전기전자학회논문지
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• 제23권3호
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• pp.817-825
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• 2019

마이크로프로세서를 이용한 제어알고리즘 구현에서 차분방정식이 매우 유용하게 사용된다. 샘플링 데이터로부터 미분 값을 추정하기 위해 전향, 후향 및 중심 차분 방식이 사용되어왔다. 차분 값을 계산하기 위해서는 차분계수가 매우 중요하다. 본 논문에서는 유한 차분 계수를 계산하기 위한 새로운 방식을 제시하고자 한다. 제안된 방식의 유효성을 입증하기 위해 RLS 알고리즘을 적용한 파라미터 추정에 대하여 적용하였다.

• 한국산업융합학회 논문집
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• 제25권6_3호
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• pp.1293-1302
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• 2022

The relationship between homeownership and participation in giving and volunteering overall indicates that homeowners are more likely to give and participate in volunteering organizations than renters. This study compared 'giving and participation in volunteering between homeowners(n=6,078) and renters(3,587) in the 14^th Korean Welfare Panel Survey data collected in 2019. The outcome measure of study is a binary outcome of giving and volunteering participation. This study accounted for a bias arising from selection on observables. Specifically, this study employed a recursive bivariate probit model to simultaneously estimate respondents' participation in giving and volunteering participation and their selection of homeownership. Findings from this study have provided some evidence that homeowners and renters have different behaviors in giving and volunteering participation. Finally, issues relating to homeownership and social outcomes were discussed. Implications for social work practice and research were further discussed.

• International journal of advanced smart convergence
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• 제11권4호
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• pp.28-40
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• 2022

Although precise temperature control in the heat treatment process is a key factor in process reliability, there are many cases where there is no separate heat source control optimization system in the field. To solve this problem, the program monitors the temperature data according to the heat source change through sensor communication in a recursive method based on multiple variables that affect the process, and the target heat source value and the actual heat treatment heat source to match the internal air temperature and material temperature. A control optimization system was constructed. Through this study, the error rate between the target temperature and the atmosphere (material surface) temperature of around 10.7% with the existing heat source control method was improved to an improved result of around 0.1% using a process optimization algorithm and system.

• 한국정밀공학회지
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• 제14권2호
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• pp.160-168
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• 1997

A $H_{\infty}$self-tuning control scheme for the tip position of a flexible link robot handling unknown loads is presented here. The scheme essentially comprises a recursive least-squares identification algorithm and $H_{\infty}$self-tunning controller. The $H_{\infty}$control low is designed to be robust to uncertain parameters and the self-tunning action provides adaption to unknown parameters. Through numerical study, the performance comparison of the $H_{\infty}$self-tuning controller with a constant gain $H_{\infty}$controller as well as a LQG self-tuning controller clearly shows its superior ability in handling load changes in quiescent states.nt states.

• 한국정밀공학회지
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• 제11권6호
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• pp.136-142
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• 1994

This study presents an algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is described for te weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions are extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted real-time signal processing, which are high precision and stability in noisy environment.

• Journal of applied mathematics & informatics
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• 제18권1_2호
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• pp.377-381
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• 2005

We present a convenient recursive formula for the sums of alternating harmonic series of odd order. The recursion is obtained by expanding in Fourier series certain elementary functions.

• 충청수학회지
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• 제34권3호
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• pp.253-257
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• 2021

In this paper, we provide a recursive formula for the number of involutions of doubly alternating Baxter permutations in S_n.

• Transactions on Control, Automation and Systems Engineering
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• 제4권2호
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• pp.124-129
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• 2002

This paper demonstrates that the largest Lyapunov exponent λ of recurrent neural networks can be controlled efficiently by a stochastic gradient method. An essential core of the proposed method is a novel stochastic approximate formulation of the Lyapunov exponent λ as a function of the network parameters such as connection weights and thresholds of neural activation functions. By a gradient method, a direct calculation to minimize a square error (λ - λ$\^$obj/)$^2$, where λ$\^$obj/ is a desired exponent value, needs gradients collection through time which are given by a recursive calculation from past to present values. The collection is computationally expensive and causes unstable control of the exponent for networks with chaotic dynamics because of chaotic instability. The stochastic formulation derived in this paper gives us an approximation of the gradients collection in a fashion without the recursive calculation. This approximation can realize not only a faster calculation of the gradient, but also stable control for chaotic dynamics. Due to the non-recursive calculation. without respect to the time evolutions, the running times of this approximation grow only about as N$^2$ compared to as N$\^$5/T that is of the direct calculation method. It is also shown by simulation studies that the approximation is a robust formulation for the network size and that proposed method can control the chaos dynamics in recurrent neural networks efficiently.