• Journal of applied mathematics & informatics
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• v.6 no.2
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• pp.369-378
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• 1999

In This study we examine the applicability of Newton's method and the modified Newton's method for a, pp.oximating a lo-cally unique solution of a nonlinear equation in a Banach space. We assume that the newton-Kantorovich hypothesis for Newton's method is violated but the corresponding condition for the modified Newton method holds. Under these conditions there is no guaran-tee that Newton's method starting from the same initial guess as the modified Newton's method converges. Hence it seems that we must always use the modified Newton method under these condi-tions. However we provide a numerical example to demonstrate that in practice this may not be a good decision.

• Journal of applied mathematics & informatics
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• v.33 no.1_2
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• pp.127-143
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• 2015

In this paper, we consider a modified inexact Newton method for solving a nonlinear system F(x) = 0 where $F(x):R^n{\rightarrow}R^n$. The basic idea is to accelerate convergence. A semi-local convergence theorem for the modified inexact Newton method is established and an affine invariant version is also given. Moreover, we test three numerical examples which show that the modified inexact scheme is more efficient than the classical inexact Newton strategy.

• The Pure and Applied Mathematics
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• v.15 no.1
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• pp.35-45
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• 2008

In cases sufficient conditions for the semilocal convergence of Newtonlike methods are violated, we start with a modified Newton-like method (whose weaker convergence conditions hold) until we stop at a certain finite step. Then using as a starting guess the point found above we show convergence of the Newtonlike method to a locally unique solution of a nonlinear operator equation in a Banach space setting. A numerical example is also provided.

• East Asian mathematical journal
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• v.25 no.2
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• pp.147-151
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• 2009

We use an improved Newton-Kantorovich theorem introduced in [2] to analyze interior point methods. Our approach requires less number of steps than before [5] to achieve a certain error tolerance for both Newton's and Modified Newton's methods.

• The Pure and Applied Mathematics
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• v.16 no.4
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• pp.405-416
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• 2009

In this study we are concerned with the problem of approximating a locally unique solution of an equation in a Banach space setting using Newton's and modified Newton's methods. We provide weaker convergence conditions for both methods than before [5]-[7]. Then, we combine Newton's with the modified Newton's method to approximate locally unique solutions of operator equations. Finer error estimates, a larger convergence domain, and a more precise information on the location of the solution are obtained under the same or weaker hypotheses than before [5]-[7]. The results obtained here improve our earlier ones reported in [4]. Numerical examples are also provided.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.339-344
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• 2000

Newton-Raphson 기법은 구조물의 비선형 해석에 널리 쓰이는 반복계산기법이다. 비선형 해석을 위한 반복계산기법은 컴퓨터의 발달을 감안해도 상당한 계산시간이 소요된다. 본 논문에서는 신경회로망 예측을 사용한 Predicted Newton-Raphson 반복계산기법을 제안하였다. 통상적인 Newton-Raphson 기법은 이전스텝에서 수렴된 점으로부터 현재 스텝의 반복계산을 시작하는 반면 제시된 방법은 현재 스텝 수렴해에 대한 예측점에서 반복계산을 시작한다. 수렴해에 대한 예측은 신경회로망을 사용하여 이전 스텝 수렴해의 과거경향을 파악한 후 구한다. 반복계산 시작점이 수렴점에 보다 근접하여 위치하므로 수렴속도가 빨라지게 되고 허용되는 하중스텝의 크기가 커지게 된다. 또한 반복계산의 시작점으로부터 이루어지는 계산과정은 통상적인 Newton-Raphson 기법과 동일하므로 기존의 Newton-Raphson 기법과 정확히 일치하는 수렴해를 구할 수 있다. 구조물의 정적 비선형 거동에 대한 수치해석을 통하여 modified Newton-Raphson 기법과 제시된 Predicted Newton=Raphson 기법의 정확성과 효율성을 비교하였다. 제시된 Predicted Newton-Raphson 기법은 modified Newton-Raphson 기법과 동일한 해를 산출하면서도 계산상의 효율성이 매우 큼을 확인할 수 있었다.

• East Asian mathematical journal
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• v.24 no.2
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• pp.161-168
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• 2008

We revisit the study of finding solutions of equations containing a differentiable and a continuous term on a Banach space setting [1]-[5], [9]-[11]. Using more precise majorizing sequences than before [9]-[11], we provide a semilocal convergence analysis for the generalized Newton's method as well the generalized modified Newton's method. It turns out that under the same or even weaker hypotheses: finer error estimates on the distances involved, and an at least as precise information on the location of the solution can be obtained. The above benefits are obtained under the same computational cost.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.32-35
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• 2004

In boundary estimation in Electrical Impedance Tomography (EIT), conventional method is the modified Newton Raphson (mNR) method .The mNR is famous for good method since has good convergence and robustness against noisy data. But the mNR is low efficiency to get and update Jacobian matrix. So, the mNR become very slow algorithm. We propose the Quasi Newton (QN) method to improve efficiency which will lead to speed up in boundary estimation. The QN can improve a low efficiency by using estimated Jacobian matrix contrary to using exactly calculated Jacobian matrix, this used by the mNR. And finally, we propose the modified Quasi Newton (mQN) method because the QN has some problems such as bad early convergence rate and instability of 'divided by zero'. For the verification of the propose method, numerical experiments are conducted and the results show a good performance.

• East Asian mathematical journal
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• v.24 no.2
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• pp.151-159
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• 2008

An error analysis introduced in [1], [2] is utilized in combination with nondiscrete mathematical induction to provide a finer than before [3]-[7], [11] semilocal convergence analysis for a certain class of modified Newton processes.

• East Asian mathematical journal
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• v.35 no.3
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• pp.341-349
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• 2019

In this paper, we are concerned with the minimal positive solution to system of the nonlinear matrix equations $A_1X^2+B_1Y +C_1=0$ and $A_2Y^2+B_2X+C_2=0$, where $A_i$ is a positive matrix or a nonnegative irreducible matrix, $C_i$ is a nonnegative matrix and $-B_i$ is a nonsingular M-matrix for i = 1, 2. We apply Newton's method to system and present a modified Newton's iteration which is validated to be efficient in the numerical experiments. We prove that the sequences generated by the modified Newton's iteration converge to the minimal positive solution to system of nonlinear matrix equations.