• Journal of Industrial Technology
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• v.22 no.B
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• pp.35-44
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• 2002

To find the optimal solution as rapidly and exactly as possible with Nelder-Mead simplex algorithm, the present values of the reflection, expansion, contraction and/or shrink parameters of this algorithm are needed to be changed at appropriate time during the search process. The reflection parameter is selected in this study in order to be changed because reflection, expansion and contraction process can be simultaneously effected by only this parameter. Two independent indices for determining whether the present value of the reflection parameter of this algorithm should be changed or not during the search process are suggested in this study. Those indices were made of the equations of Nelder-Mead simplex algorithm's convergence criterion and Dennis-Wood's convergence criterion, respectively. It is appeared that the optimal solution can be find with smaller numbers of objective function evaluation than the original Nelder-Mead's one with fixed parameter when the those indices are used during the search process. and the more remarkable reduction effect of the number of an objective function evaluation can be obtained when the latter index is used.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.10
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• pp.740-747
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• 1988

This paper describes the parameter convergence property for an adaptive identifier and deals with the stability of the adaptive system in terms of the general error model. The Persistent Excitation (PE) condition to guarantee parameter convergence is derived using the Power Spectrum Analysis. In the adaptive identifier designed under the assumptions that the plant has not unmodelled dynamics, it can be shown that the equilibrium points of adjustable parameters are independent on the position or the number of input spectrums, if the adaptive signal is PE. When the plant contains unmodelled dynamics and the same controller is used, the PE condition can still hold but the parameter tuned values are changed with the spectrum.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.101-124
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• 2002

The convergence rate of a numerical procedure barred on Schwarz Alternating Method (SAM) for solving elliptic boundary value problems (BVP's) depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It hee been observed that the Robin condition(mixed interface condition), controlled by a parameter, can optimize SAM's convergence rate. Since the convergence rate is very sensitive to the parameter, Tang[17] suggested another interface condition called over-determined interface condition. Based on the over-determined interface condition, we formulate the two-layer multi-parameterized SAM. For the SAM and the one-dimensional elliptic model BVP's, we determine analytically the optimal values of the parameters. For the two-dimensional elliptic BVP's , we also formulate the two-layer multi-parameterized SAM and suggest a choice of multi-parameter to produce good convergence rate .

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.721-723
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• 1987

An Adaptation algorithm is presented and a convergence criterion is derived for parallel model reference adaptive bilinear systems. The output error converges asymptotically to zero, and the parameter estimates are bounded for stable reference models. The convergence criterion depends only upon the input sequence and a priori estimates of the maximum parameter values.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.26-32
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• 1994

The Lloyd-Max algorithm is an iterative scheme for design of the minimum mean square error quantizer. It is very simple in concept and easy to program into a computer. However its convergence and accuracy are primarily dependent upon the accuracy of the initial parameter. In this paper, a new initial parameter which converges to a specific value when the number of output levels becomes large is selected. And an estimator using curve fitting techique is suggested. In addition, performance of the proposed method is shown to be superior to that of the existing methods in accuracy and convergence.

• Journal of the Korean Mathematical Society
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• v.53 no.3
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• pp.691-707
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• 2016

In this paper, we first introduce two one-parameter relaxation (OPR) iterative methods for solving singular saddle point problems whose semi-convergence rate can be accelerated by using scaled preconditioners. Next we present formulas for finding their optimal parameters which yield the best semi-convergence rate. Lastly, numerical experiments are provided to examine the efficiency of the OPR methods with scaled preconditioners by comparing their performance with the parameterized Uzawa method with optimal parameters.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.305-317
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• 2004

We construct the empirical Bayes (EB)estimation of the parameter in two-side truncated distribution families with asymmetric Linex loss using negatively associated (NA) samples. The asymptotical optimality and convergence rate of the EB estimation is obtained. We will show that the convergence rate can be arbitrarily close to $O(n^{-q}),\;q\;=\;{\lambda}s(\delta\;-\;2)/\delta(s\;+\;2)$.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.285-294
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• 2007

In this paper, we investigate a novel online estimation algorithm for dynamic Bayesian network(DBN) parameters, given as conditional probabilities. We sequentially update the parameter adjustment rule based on observation data. We apply our algorithm to two well known representations of DBNs: to a first-order Markov Chain(MC) model and to a Hidden Markov Model(HMM). A sliding window allows efficient adaptive computation in real time. We also examine the stochastic convergence and stability of the learning algorithm.

• Journal of the Korean Mathematical Society
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• v.51 no.1
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• pp.137-162
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• 2014

In this work we study the local and semilocal convergence of the relaxed Newton's method, that is Newton's method with a relaxation parameter 0 < ${\lambda}$ < 2. We give a Kantorovich-like theorem that can be applied for operators defined between two Banach spaces. In fact, we obtain the recurrent sequence that majorizes the one given by the method and we characterize its convergence by a result that involves the relaxation parameter ${\lambda}$. We use a new technique that allows us on the one hand to generalize and on the other hand to extend the applicability of the result given initially by Kantorovich for ${\lambda}=1$.

• 한국전산유체공학회:학술대회논문집
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• 2003.08a
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• pp.49-55
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• 2003

A comprehensive study has been made for the investigation of the convergence characteristics of the LU scheme for the Euler equations using von Neumann stability analysis. The stability results indicate that the convergence rate is governed by a specific parameter combination. Based on this insight it is shown that the LU scheme will not suffer convergence deterioration at any grid aspect ration if the local time step is defined using appropriate parameter combination. The numerical results demonstrate that this time step definition gives uniform convergence for grid aspect ratios from one to $1\times10^4$.