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Vector Fitting vs. Levenberg-Marquardt : Some experiments
2009 IEEE Workshop on Signal Propagation on Interconnects, 2009A discussion and evaluation of the Vector Fitting technique is presented, in comparison with a special flavor of the Levenberg-Marquardt method, which is one of the most successful quasi Gauss-Newton techniques. Although generally slower than Vector Fitting, the Levenberg-Marquardt method can achieve greater accuracy than Vector Fitting, because of its
Knockaert, Luc +2 more
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Cornering stiffness estimation using Levenberg–Marquardt approach
Inverse Problems in Science and Engineering, 2021Study of vehicle dynamics aggregates possibilities to enhance performance, safety and reliability, such as the integration of control systems, usually requiring knowledge on vehicle's states and pa...
Camila Leão Pereira +2 more
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A Levenberg–Marquardt algorithm for unconstrained multicriteria optimization
Operations Research Letters, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fischer, Andreas, Shukla, Pradyumn K.
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Levenberg-Marquardt method for ANFIS learning
Proceedings of North American Fuzzy Information Processing, 2002Presents the results of applying the Levenberg-Marquardt method (K. Levenberg, 1944, and D.W. Marquardt, 1963), which is a popular nonlinear least-squares method, to the ANFIS (Adaptive Neuro-Fuzzy Inference System) architecture proposed by Jang (IEEE Trans. on Systems, Man and Cybernctics, vol. 23, no. 3, pp 665-685, May 1993).
null Jyh-Shing Roger Jang, E. Mizutani
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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 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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Damage Localization Using Levenberg-Marquardt Optimization
Key Engineering Materials, 2007In this paper, an optimal solution method is proposed for determining the location of change, i.e. damage, within a perturbed system utilizing a nonlinear pseudo-second order search algorithm based on function evaluations and gradient information.
Danny L. Parker +2 more
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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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Levenberg-Marquardt training for modular networks
Proceedings of International Conference on Neural Networks (ICNN'96), 2002The modular neural network has been shown to be an effective alternative to multilayer feedforward networks, especially for implementing functions with sharp changes. This paper describes a new method for training modular networks, based on the Levenberg-Marquardt algorithm for nonlinear least squares.
null Meng-Hock Fun, M.T. Hagan
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