• Journal of the Chungcheong Mathematical Society
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• v.23 no.4
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• pp.845-852
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• 2010

A nonlinear algebraic equation f(x) = 0 is considered to find a root with integer multiplicity $m{\geq}1$. A variant of Newton-secant method for a multiple root is proposed below: for n = 0, 1, $2{\cdots}$ $$x_{n+1}=x_n-\frac{f(x_n)^2}{f^{\prime}(x_n)\{f(x_n)-{\lambda}f(x_n-\frac{f(x_n)}{f^{\prime}(x_n)})\}$$, $$\lambda=\{_{1,\;if\;m=1.}^{(\frac{m}{m-1})^{m-1},\;if\;m{\geq}2$$ It is shown that the method has third-order convergence and its asymptotic error constant is expressed in terms of m. Numerical examples successfully verified the proposed scheme with high-precision Mathematica programming.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.557-562
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• 1991

In this paper, we present new methods for solving the inverse kinematics associated with 6 degree of freedoms manipulator by the numerical method. This method will be based on tracking stability of special nonlinear dynamical systems, and differs from the typical techniques based by the Newton-Gauss or Newton-Raphson method for solving nonlinear equations. This simulation results show that the new method is solving the inverse kinematics of PUMA 560 without the derivative of a given task space trajectories.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.971-980
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• 2012

In this paper, a method associating with one new form of nonmonotone linesearch technique is proposed, which can be regarded as a generalization of the Perry-Shanno memoryless quasi-Newton type method. Under some reasonable conditions, the global convergence of the proposed method is proven. Numerical tests show its efficiency.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.401-410
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• 2004

We address the problem of parameter estimation in multivariate distributions under ignorable non-monotone missing data. The factoring likelihood method for monotone missing data, termed by Rubin (1974), is extended to a more general case of non-monotone missing data. The proposed method is algebraically equivalent to the Newton-Raphson method for the observed likelihood, but avoids the burden of computing the first and the second partial derivatives of the observed likelihood. Instead, the maximum likelihood estimates and their information matrices for each partition of the data set are computed separately and combined naturally using the generalized least squares method.

• 전기의세계
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• v.26 no.2
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• pp.78-83
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• 1977

The Newton-Raphson method has now gained widespread popularity in Load-flow calculationes. In this paper programming is developed with aims to improve the convergence characteristics, speed and memory requirements in the above method. The method of Load-flow calculations is performed by employing the MW-O/MVAR-V decoupling principle. To reduce the memory requirements and improve the speed of calculation the programming of the Optimally Ordered Triangular Factorization method is developed. Besides this, other measures are taken to reduce memory requirements and computing time and to improve reliability. KECO'S 48 Bus system was tested and the method suggested in this paper was proved to be faster than any other methods.

• East Asian mathematical journal
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• v.29 no.5
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• pp.503-510
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• 2013

A quadratic B-spline finite element method for the spatial variable combined with a Newton method for the time variable is proposed to approximate a solution of Benjamin-Bona-Mahony-Burgers (BBMB) equation. Two examples were considered to show the efficiency of the proposed scheme. The numerical solutions obtained for various viscosity were compared with the exact solutions. The numerical results show that the scheme is efficient and feasible.

• Journal of the Chungcheong Mathematical Society
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• v.24 no.3
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• pp.437-447
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• 2011

In this paper we present a new variant of the Euler-Chebyshev method for solving nonlinear equations. Analysis of convergence is given to show that the presented methods are at least fifth-order convergent. Several numerical examples are given to illustrate that newly presented methods can be competitive to other known fifth-order methods and the Newton method in the efficiency and performance.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.29-40
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• 2000

We provide semilocal convergence theorems for Newton-like methods in Banach space using outer and generalized inverses. In contrast to earlier results we use hypotheses on the second instead of the first Frechet-derivative. This way our Newton-Kantorovich hypotheses differ from earlier ones. Our results can be used to solve undetermined systems, nonlinear least square problems and ill-posed nonlinear operator equations.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.7 no.1
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• pp.7-14
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• 2003

The main concern of this paper is to develop a new class of quasi-newton methods. These methods are intended for use whenever memory space is a major concern and, hence, they are usually referred to as limited memory methods. The methods developed in this work are sensitive to the choice of the memory parameter ${\eta}$ that defines the amount of past information stored within the Hessian (or its inverse) approximation, at each iteration. The results of the numerical experiments made, compared to different choices of these parameters, indicate that these methods improve the performance of limited memory quasi-Newton methods.

• East Asian mathematical journal
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• v.27 no.5
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• pp.521-525
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• 2011

We use a weaker version of the celebrated Newton-Kantorovich theorem [3] reported by us in [1] to find solutions of discrete dynamical systems involving operators with chaotic behavior. Our results are obtained by extending the application of the shadowing lemma [4], and are given under the same computational cost as before [4]-[6].