• Title/Summary/Keyword: Newton iterative

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A NEWTON-IMPLICIT ITERATIVE METHOD FOR NONLINEAR INVERSE PROBLEMS

  • Meng, Zehong;Zhao, Zhenyu
    • Journal of applied mathematics & informatics
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    • v.29 no.3_4
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    • pp.909-920
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    • 2011
  • A regularized Newton method for nonlinear ill-posed problems is considered. In each Newton step an implicit iterative method with an appropriate stopping rule is proposed and analyzed. Under certain assumptions on the nonlinear operator, the convergence of the algorithm is proved and the algorithm is stable if the discrepancy principle is used to terminate the outer iteration. Numerical experiment shows the effectiveness of the method.

A Formulation of Iterative Eigenvalue Analysis Algorithm to the Second Order Newton Raphson Method (반복계산에 의한 고유치 해석 알고리즘의 2차 뉴튼랩슨법으로의 정식화)

  • Kim, Deok-Yeong
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.3
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    • pp.127-133
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    • 2002
  • This paper presents an efficient improvement of the iterative eigenvalue calculation method of the AESOPS algorithm. The intuitively and heuristically approximated iterative eigenvalue calculation method of the AESOPS algorithm is transformed to the Second Order Newton Raphson Method which is generally used in numerical analysis. The equations of second order partial differentiation of external torque, terminal and internal voltages are derived from the original AESOPS algorithm. Therefore only a few calculation steps are added to transform the intuitively and heuristically approximated AESOPS algorithm to the Second Order Newton Raphson Method, while the merits of original algorithm are still preserved.

AN ERROR ANALYSIS FOR A CERTAIN CLASS OF ITERATIVE METHODS

  • Argyros, Ioannis K.
    • Journal of applied mathematics & informatics
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    • v.8 no.3
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    • pp.743-753
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    • 2001
  • We provide local convergence results in affine form for inexact Newton-like as well as quasi-Newton iterative methods in a Banach space setting. We use hypotheses on the second or on the first and mth Frechet-derivative (m≥2 an integer) of the operator involved. Our results allow a wider choice of starting points since our radius of convergence can be larger than the corresponding one given in earlier results using hypotheses on the first-Frechet-derivative only. A numerical example is provided to illustrate this fact. Our results apply when the method is, for example, a difference Newton-like or update-Newton method. Furthermore, our results have direct applications to the solution of autonomous differential equations.

Comparison of Parameter Estimation for Weibull Distribution

  • Wang, Fu-Kwun;J. Bert Keats;B. Y. Leu
    • International Journal of Reliability and Applications
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    • v.4 no.1
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    • pp.41-50
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    • 2003
  • This paper represents the first comprehensive comparison of the Newton-Raphson's method and Simple Iterative Procedure (SIP) in the maximum likelihood estimation of the two-parameter Weibull distribution. Computer simulation is employed to compare these two methods for multiply censored, singly censored data (Type I or Type Ⅱ censoring) and complete data. Results indicate the Newton-Raphson's with the Menon's estimated value, as an initial point remains the effective iterative procedure for estimating the parameters.

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HIGH-ORDER NEWTON-KRYLOV METHODS TO SOLVE SYSTEMS OF NONLINEAR EQUATIONS

  • Darvishi, M.T.;Shin, Byeong-Chun
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.15 no.1
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    • pp.19-30
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    • 2011
  • In [21], we compared the Newton-Krylov method and some high-order methods to solve nonlinear systems. In this paper, we propose high-order Newton-Krylov methods combining the Newton-Krylov method with some high-order iterative methods to solve systems of nonlinear equations. We provide some numerical experiments including comparisons of CPU time and iteration numbers of the proposed high-order Newton-Krylov methods for several nonlinear systems.

SOLVING A MATRIX POLYNOMIAL BY NEWTON'S METHOD

  • Han, Yin-Huan;Kim, Hyun-Min
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.14 no.2
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    • pp.113-124
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    • 2010
  • We consider matrix polynomial which has the form $P_1(X)=A_oX^m+A_1X^{m-1}+...+A_m=0$ where X and $A_i$ are $n{\times}n$ matrices with real elements. In this paper, we propose an iterative method for the symmetric and generalized centro-symmetric solution to the Newton step for solving the equation $P_1(X)$. Then we show that a symmetric and generalized centro-symmetric solvent of the matrix polynomial can be obtained by our Newton's method. Finally, we give some numerical experiments that confirm the theoretical results.

A Study on Interpretation of Gravity Data by using Iterative Inversion Methods (반복적(反復的) 역산법(逆算法)에 의(依)한 중력자료(重力資料)의 해석(解析)에 관(關)한 연구(硏究))

  • Roh, Cheol-Hwan;Yang, Sung-Jin;Shin, Chang-Soo
    • Economic and Environmental Geology
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    • v.22 no.3
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    • pp.267-276
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    • 1989
  • This paper presents results of interpretaton of gravity data by iterative nonlinear inversion methods. The gravity data are obtained by a theoretical formula for two-dimensional 2-layer structure. Depths to the basement of the structure are determined from the gravity data by four interative inversion methods. The four inversion methods used here are the Gradient, Gauss-Newton, Newton-Raphson, and Full Newton methods. Inversions are performed by using different initial guesses of depth for the over-determined, even-determined, and under-determined cases. This study shows that the depth can be determined well by all of the methods and most efficiently by the Newton-Raphson method.

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A Predicted Newton-Raphson Iterative Method utilizing Neural Network (신경회로망을 이용한 예측 뉴턴-랩손 반복계산기법)

  • Kim, Jong-Hoon;Kim, Yong-Hyup
    • 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.

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Quasi-Likelihood Approach for Linear Models with Censored Data

  • Ha, Il-Do;Cho, Geon-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.219-225
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    • 1998
  • The parameters in linear models with censored normal responses are usually estimated by the iterative maximum likelihood and least square methods. However, the iterative least square method is simple but hardly has theoretical justification, and the iterative maximum likelihood estimating equations are complicatedly derived. In this paper, we justify these methods via Wedderburn (1974)'s quasi-likelihood approach. This provides an explicit justification for the iterative least square method and also directly the iterative maximum likelihood method for estimating the regression coefficients.

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2D Image Reconstruction of Earth Model by Electrical Resistance Tomography (ERT를 이용한 2차원 대지모델 영상복원)

  • Boo, Chang-Jin;Kim, Ho-Chan;Kang, Min-Jae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.7
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    • pp.3460-3467
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    • 2013
  • The In this paper, we have made numerical experiments to compare 2D image reconstruction algorithm of earth model by electrical resistance tomograpy (ERT). Gauss-Newton, simultaneous iterative reconstruction technieque (SIRT) and truncated least squares (TLS) approaches for Wenner and Schlumberger electrode arrays are presented for the solution of the ERT image reconstruction. Computer simulations show that the Gauss-Newton and TLS approach in ERT are proper for 2D image reconstruction of an earth model.