Description: 使用Levenberg-Marquart算法（最小二乘法）对BP神经网络进行训练，克服了传统BP算法收敛慢，容易收敛于局部最小值等缺点-use Levenberg-Marquardt algorithm to overcome some disadvantages like slow convergence which traditional BP neural network usually has Platform: |
Size: 1024 |
Author:薛正 |
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Description: LM算法
老外写的The Levenberg-Marquardt (LM) algorithm is the most widely used optimization algorithm. It
outperforms simple gradient descent and other conjugate gradient methods in a wide variety of
problems. This document aims to provide an intuitive explanation for this algorithm. The LM
algorithm is fi rst shown to be a blend of vanilla gradient descent and Gauss-Newton iteration.
Subsequently, another perspective on the algorithm is provided by considering it as a trust-region
method-The Levenberg-Marquardt (LM) algorithm is the most widely used optimization algorithm. It
outperforms simple gradient descent and other conjugate gradient methods in a wide variety of
problems. This document aims to provide an intuitive explanation for this algorithm. The LM
algorithm is fi rst shown to be a blend of vanilla gradient descent and Gauss-Newton iteration.
Subsequently, another perspective on the algorithm is provided by considering it as a trust-region
method Platform: |
Size: 31744 |
Author:TANG |
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Description: a sparse implementation of the Levenberg Marquadt algorithm for the PARAFAC model and a multi-way incomplete data generator for Matlab. Platform: |
Size: 11264 |
Author:ria |
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Search - Levenberg-Marquart algorithm