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Hepatitis B, Hepatitis C, and HIV Seroprevalence and Their Association with Dialysis Adequacy and Glycaemic Parameters in Haemodialysis Patients: A Cross-Sectional Study from Somalia. [PDF]
Int J Gen MedÖzcan ME, Abdi AN, Doğan S.
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The Cox-Aalen Rate Model for Recurrent Events With an Informative Terminal Event. [PDF]
Stat MedYue M, Chen X, Chen J, Sun L.
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Impact of ISTA and FISTA iterative optimization algorithms on electrical impedance tomography image reconstruction. [PDF]
J Electr BioimpedanceNguyen Diep QT +5 more
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Improvements of the Newton–Raphson method
Journal of Computational and Applied Mathematics, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim-Hung Pho
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A modified Newton-Raphson method
Communications in Numerical Methods in Engineering, 2004AbstractIn this paper, we propose the following modified Newton–Raphson iteration formulation: In case r=1, the obtained formulation reduces to the Newton–Raphson formulation. The present technique circumvent pitfalls of the Newton–Raphson iteration method. Some examples are illustrated. Copyright © 2004 John Wiley & Sons, Ltd.
Ji-Huan He
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Improvements of convergence characteristics of Newton-Raphson method for nonlinear magnetic field analysis [PDF]
IEEE Transactions on Magnetics, 1992 In order to overcome the divergence of the Newton-Raphson iteration in the nonlinear magnetic field analysis, a relaxation factor is introduced and its optimum value is examined. It is shown that the modified Newton-Raphson method proposed exhibits quick
Kazuhiro Muramatsu
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Applied Numerical Mathematics, 1990
Let g: \(R^ 1\to R^ 1\) be a differentiable function. For the numerical solutions of the equation \(g(x)=0\) a randomized Newton process of the form \(X_{k+1}=x_ k-(g(x_ k)+Z_{1,k})/(g'(x_ k)+Z_{2,k}),\quad k=0,1,...,\) is considered where \(Z_{1,k}\), \(Z_{2,k}\) are mutually independent random variables with controllable densities and hence \(\{X_ k\}
Joseph, G., Levine, A., Liukkonen, J.
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Let g: \(R^ 1\to R^ 1\) be a differentiable function. For the numerical solutions of the equation \(g(x)=0\) a randomized Newton process of the form \(X_{k+1}=x_ k-(g(x_ k)+Z_{1,k})/(g'(x_ k)+Z_{2,k}),\quad k=0,1,...,\) is considered where \(Z_{1,k}\), \(Z_{2,k}\) are mutually independent random variables with controllable densities and hence \(\{X_ k\}
Joseph, G., Levine, A., Liukkonen, J.
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A geometric Newton–Raphson strategy
Computer Aided Geometric Design, 2001In the standard Newton-Raphson algorithm for solving nonlinear equations, a new guess is computed by solving a linear approximation of the problem at the current guess. A similar, very effective strategy is proposed here for solving geometric problems (e.g., finding intersections) on general plane curves.
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ON NEWTON-RAPHSON METHOD [PDF]
Journal of Information Systems and Operations Management, 2011 Recent versions of the well-known Newton-Raphson method for solving algebraic equations are presented. First of these is the method given by J. H. He in 2003. He reduces the problem to solving a second degree polynomial equation. However He’s method is not applicable when this equation has complex roots. In 2008, D. Wei, J. Wu and M.
Mircea Cirnu, Irina Badralexi
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