Results 201 to 210 of about 63,095 (231)
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Acceleration and Stabilization Techniques for the Levenberg-Marquardt Method
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2005In this paper, two techniques are proposed for accelerating and stabilizing the Levenberg-Marquardt (LM) method where its conventional stabilizer matrix (identity matrix) is superseded by (1) a diagonal matrix whose elements are column norms of Jacobian matrix J, or (2) a non-diagonal square root matrix of JTJ.
Hiroyasu Sakamoto +3 more
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The Parallel Modification to the Levenberg-Marquardt Algorithm
2018The paper presents a parallel approach to the Levenberg-Marquardt algorithm (also called LM or LMA). The first section contains the mathematical basics of the classic LMA. Then the parallel modification to LMA is introduced. The classic Levenberg-Marquardt algorithm is sufficient for a training of small neural networks.
Jaroslaw Bilski +2 more
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Some research on Levenberg–Marquardt method for the nonlinear equations
Applied Mathematics and Computation, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Changfeng Ma, Lihua Jiang
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A Levenberg–Marquardt method based on Sobolev gradients
Nonlinear Analysis: Theory, Methods & Applications, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kazemi, Parimah, Renka, Robert J.
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Nonmonotone Levenberg–Marquardt Algorithms and Their Convergence Analysis
Journal of Optimization Theory and Applications, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, J. Z., Chen, L. H.
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Multilayer Potts Perceptrons With Levenberg–Marquardt Learning
IEEE Transactions on Neural Networks, 2008This paper presents learning multilayer Potts perceptrons (MLPotts) for data driven function approximation. A Potts perceptron is composed of a receptive field and a K -state transfer function that is generalized from sigmoid-like transfer functions of traditional perceptrons.
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Global complexity bound of the Levenberg–Marquardt method
Optimization Methods and Software, 2016In this paper, we propose a new updating rule of the Levenberg–Marquardt LM parameter for the LM method for nonlinear equations. We show that the global complexity bound of the new LM algorithm is , that is, it requires at most iterations to derive the norm of the gradient of the merit function below the desired accuracy .
Ruixue Zhao, Jinyan Fan
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LMA: A generic and efficient implementation of the Levenberg–Marquardt Algorithm
Software: Practice and Experience, 2017SummaryThis paper presents an open‐source, generic and efficient implementation of a very popular nonlinear optimization method: the Levenberg–Marquardt algorithm (LMA). This minimization algorithm is well known and hundreds of implementations have already been released.
Ramadasan, Datta +2 more
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Levenberg–Marquardt method for unconstrained optimization
Tambov University Reports. Series: Natural and Technical Sciences, 2019We propose and study the Levenberg–Marquardt method globalized by means of linesearch for unconstrained optimization problems with possibly nonisolated solutions. It is well-recognized that this method is an efficient tool for solving systems of nonlinear equations, especially in the presence of singular and even nonisolated solutions.
Alexey Izmailov +2 more
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A Levenberg–Marquardt Scheme for Nonlinear Image Registration
BIT Numerical Mathematics, 2003Two images are represented by compactly supported functionals \(T,R:\Omega\to \mathbb{R}\) where \(\Omega\subset\mathbb{R}^2\). A displacement vector field \(u:\Omega\to\mathbb{R}^2\) is considered which matches the two images, \(R(x)\approx T(x- u(x))\).
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