Results 181 to 190 of about 63,095 (231)
The Impact of Collagen Fiber and Slit Orientations on Meshing Ratios in Skin Meshing Models. [PDF]
Biomimetics (Basel)Razaghi Pey Ghaleh M, O'Mahoney D.
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Tightly Coupled GNSS/IMU Hybrid Navigation Using Factor Graph Optimization with NLOS Detection Capability. [PDF]
Sensors (Basel)Tanimura H, Tsujii T.
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High-accuracy machine learning approach for predicting J-V characteristics of perovskite solar cells under variable irradiance. [PDF]
Sci RepToprak A.
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Simplified Levenberg–Marquardt Method in Hilbert Spaces
Computational Methods in Applied Mathematics, 2022Abstract In 2010, Qinian Jin considered a regularized Levenberg–Marquardt method in Hilbert spaces for getting stable approximate solution for nonlinear ill-posed operator equation F
Pallavi Mahale, Farheen M. Shaikh
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A parallel levenberg-marquardt algorithm
Proceedings of the 23rd international conference on Supercomputing, 2009This paper describes a parallel Levenberg-Marquardt algorithm that has been implemented as part of a larger system to support the kinetic modeling of polymer chemistry. The Levenberg-Marquardt algorithm finds a local minimum of a function by varying parameters of the function.
Jun Cao +4 more
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A note on the Levenberg–Marquardt parameter
Applied Mathematics and Computation, 2009The authors consider the problem of determining efficient Levenberg-Marquardt (LM) parameters for systems of nonlinear equations (1) \(F(x)= 0\), where \(F: \mathbb{R}^n\to\mathbb{R}^n\) is a continuously differentiable function, provided \(\| F(x)\|\) satisfies a local error bound condition which is weaker than nonsingularity.
Jinyan Fan, Jianyu Pan
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A smoothing Levenberg–Marquardt method for NCP
Applied Mathematics and Computation, 2006Nonlinear complementarity problems (NCPs) are converted to an equivalent system of smooth nonlinear equations by using a smoothing technique. Then a Levenberg-Marquardt type method is used to solve the system of nonlinear equations. The method has the following merits: (i) any cluster point of the iteration sequence is a solution of the \(P_{0}\)-NCP; (
Ju-Liang Zhang, Xiang-Sun Zhang
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Improved Computation for Levenberg–Marquardt Training
IEEE Transactions on Neural Networks, 2010The improved computation presented in this paper is aimed to optimize the neural networks learning process using Levenberg-Marquardt (LM) algorithm. Quasi-Hessian matrix and gradient vector are computed directly, without Jacobian matrix multiplication and storage. The memory limitation problem for LM training is solved.
Bogdan M. Wilamowski, Hao Yu
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A Levenberg-Marquardt method with approximate projections
Computational Optimization and Applications, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Roger Behling +4 more
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