Published January 1, 2018 | Version v1
Journal article

Analysis Local Convergence of Gauss-Newton Method

  • 1. Department of Mathematics, Universitas Sumatera Utara, Medan (Indonesia)

Description

The Gauss-Newton method is a very efficient, simple method used to solve nonlinear least-squares problems. This can be seen as a modification of the newton method to find the minimum value of a function. In solving nonlinear problems, the Gauss Newton Algorithm is used to minimize the sum of quadratic function values, which in its completion does not require the calculation or estimate of the derivatives of the two functions f (x) hence numerically more efficient with direct or iterative processes. The Gauss Newton method studied in this study is restricted to functions of one or two variables. The results of Gauss Newton's method analysis consisted of convergence at simple roots and multiple roots. Newton's method often converges quickly, especially when the iteration begins to be close enough to the desired root. However, if iteration begins far from the searched root, this method can be missed without warning. Implementation of this method usually detects and overcomes the convergence failures. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1757-899X/300/1/012044

Additional details

Publishing Information

Journal Title
IOP Conference Series. Materials Science and Engineering (Online)
Journal Volume
300
Journal Issue
1
Journal Page Range
[6 p.]
ISSN
1757-899X

Conference

Title
4. International Conference on Operational Research (InteriOR)
Dates
21-23 Aug 2017
Place
Medan (Indonesia)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52072465
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ALGORITHMS; COMPUTERIZED SIMULATION; CONVERGENCE; IMPLEMENTATION; LEAST SQUARE FIT; NEWTON METHOD; NONLINEAR PROBLEMS
Descriptors DEC
CALCULATION METHODS; ITERATIVE METHODS; MATHEMATICAL LOGIC; MATHEMATICAL SOLUTIONS; MAXIMUM-LIKELIHOOD FIT; NUMERICAL SOLUTION; SIMULATION