Results 211 to 220 of about 62,442 (223)

A Levenberg-Marquardt method with approximate projections

Computational Optimization and Applications, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Behling, R., Fischer, A., Herrich, M., Iusem, A., Ye, Y.   +4 more
openaire   +2 more sources

Convergence analysis of the Levenberg–Marquardt method

Optimization Methods and Software, 2007
The Levenberg-Marquardt method is a popular method for both optimization problems and equilibrium problems in dynamical systems. In this article, we study the convergence properties of the Levenberg-Marquardt method with the standard matrix update scheme.
Xin-Long Luo, Li-Zhi Liao, Hon Wah Tam
openaire   +1 more source

A Levenberg–Marquardt Scheme for Nonlinear Image Registration

BIT Numerical Mathematics, 2003
Two 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, \(R(x)\approx T(x- u(x))\).
openaire   +1 more source

Global Complexity Bound of the Inexact Levenberg–Marquardt Method

Journal of the Operations Research Society of China, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Huang, Jian-Chao, Fan, Jin-Yan
openaire   +1 more source

A smoothing Levenberg–Marquardt algorithm for semi-infinite programming

Computational Optimization and Applications, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jin, Ping, Ling, Chen, Shen, Huifei
openaire   +1 more source

Parallel Levenberg-Marquardt Algorithm Without Error Backpropagation

2017
This paper presents a new parallel architecture of the Leven-berg-Marquardt (LM) algorithm for training fully connected feedforward neural networks, which will also work for MLP but some cells will stay empty. This approach is based on a very interesting idea of learning neural networks without error backpropagation. The presented architecture is based
Jarosław Bilski, Bogdan M. Wilamowski
openaire   +1 more source

Levenberg Marquardt algorithm based economic load dispatch

2006 IEEE Power India Conference, 2006
This paper presents Levenberg Marquardt algorithm based multi-layer feed-forward neural network for economic load dispatch, which is trained to provide the optimal value of lambda and economic generation allocation on all the committed generating units for a given power demand. Since the training of the ANN is extremely fast, it may be used for on-line
null Krishna Teerth Chaturvedi, null Laxmi Srivastava, null Manjaree Pandit   +2 more
openaire   +1 more source

Distributed model calibration using Levenberg-Marquardt algorithm

SPIE Proceedings, 2007
The number of tunable parameters increases dramatically as we push forward to the next node of hyper-NA immersion lithography. It is very important to keep the lithographic process model calibration time under control, and its end result insensitive to either the starting point in the parameter space or the noise in the measurement data. For minimizing
Mark Lu, Liang Zhu, Li Ling, Gary Zhang, Walter Chan, Xin Zhou   +5 more
openaire   +1 more source

Modified Levenberg Marquardt Algorithm for Inverse Problems

2010
The Levenberg Marquardt (LM) algorithm is a popular nonlinear least squares optimization technique for solving data matching problems. In this method, the damping parameter plays a vital role in determining the convergence of the system. This damping parameter is calculated arbitrarily in the classical LM, causing it to converge prematurely when used ...
Muthu Naveen, Shankar Jayaraman, Vinay Ramanath, Shamik Chaudhuri   +3 more
openaire   +1 more source

Image mosaic via improved Levenberg-Marquardt algorithm

Journal of Computer Applications, 2009
Teng-jiao WANG, Li-zhi CHENG
openaire   +1 more source