| 1. | Levenberg - marquardt method is one of the most important methods for solving systems of nonlinear equations
Levenberg - marquardt方法是求解非线性方程组的最重要的方法之一。 |
| 2. | Levenberg - marquart algorithm is used in transformer online fault diagnosis , acquiring satisfied result
本文将该算法用于变压器的在线实时故障诊断中，取得了较满意的效果。 |
| 3. | Levenberg - marquart optimized algorithm was used to learn the network , and its constringency is rapid
网络的学习算法采用levenberg - marquart优化算法(简称l - m算法) ，收敛速度快，能满足实时性要求。 |
| 4. | This paper presents a new model to predict the annual maximum ice - thickness by means of combining levenberg - marquardt neural network ( nn ) with time serial method
本文将l - m神经网络与时序分析方法相结合提出一种新的模型，用于年极值冰厚预测。 |
| 5. | In order to improve the learning rate of backpropagation neural network , levenberg - marquart algorithm was proposed to learning network optimized weight parameters
为了提高bp网络的学习效率，本文将levenberg - marquart ( l - m )算法引入到bp网络中进行网络权值的学习。 |
| 6. | Ann is trained through fast bp algorithm with variable learning rate that mixed with momentum factor and levenberg - marquardt algorithm . these algorithms can improve network ' s convergence speed
算法上采用含有动量因子的自适应调整学习率的变学习率算法或levenberg一marquardi优化方法对网络进行训练，以提高网络的收敛速度。 |
| 7. | An updated - latin hypercube sampling and calculated data based on wave motion theories are adapted for efficient generation of the patterns of training the neural network . the levenberg - marquardt algorithms was applied to modify the weight matrices of neural network
采用修正的latin超立方采样技术和波动理论的计算数据来形成网络的输入和输出数据，用lm算法训练网络，改善了网络训练的收敛性能。 |
| 8. | We compose a neural network in which the input signals are the frame substructure natural frequencies and mode shapes , and output signals are the submatrix scaling factor . the levenberg - marquardt algorithms is applied to modify the weight matrices of neural network
框架子结构在动载作用下的自振频率和模态作为网络的输入，子矩阵参与系数作为网络的输出，用levenberg一marquardi算法训练网络。 |
| 9. | 2d continues gabor wavelets and levenberg - marquardt ( lm ) algorithm are used to automatically abstract features by optimize gabor wavelet ' s parameters of translation , orientation , and scale to make it approximates a local image contour region
论文采用了二维连续gabor小波，通过levenberg - marquardt ( lm )优化方法对小波滤波器的位置、尺度、方位等参数进行优化，使之与图像的轮廓特征一致，实现自动提取目标特征的目的。 |
| 10. | Fan and yuan [ 6 ] uses another method that has proved under the local error bound condition , if we choice the parameter as the norm of the function , the sequence produced by the levenberg - marquardt method converges quadraticlly to a solution of the system of the equations
如此选取参数有一些不足之处。范、袁在[ 6 ]中用另一种方法证明了当迭代参数为当前迭代点处函数值的模时， levenberg - marquardt方法具有二阶收敛性。 |
