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[Other resourceBPmatlab

Description: matlab使用BP网络的例子,使用Levenberg Marquardt算法提高训练速度,效果不错-use Matlab BP example, the use of Levenberg Marquardt algorithm to improve training speed, good results
Platform: | Size: 4378 | Author: 汤泽世 | Hits:

[Other resourcedigital_recogonizer

Description: 神经网络进行手写数字识别: 本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值. 带有图形界面-neural network handwritten numeral recognition : this program is the BP algorithm Demonstration Program, The Levenberg-Marquardt algorithm is practical value. with a graphical interface
Platform: | Size: 132910 | Author: HK | Hits:

[File OperateNEURAL+NETWORK

Description: bp神经网络算法是解决最优化问题的先进算法之一,本论文讨论了神经网络中使用最为广泛的前馈神经网络。其网络权值学习算法中影响最大的就是误差反向传播算法(back-propagation简称BP算法)。BP算法存在局部极小点,收敛速度慢等缺点。基于优化理论的Levenberg-Marquardt算法忽略了二阶项。该文讨论当误差不为零或者不为线性函数即二阶项S(W)不能忽略时的Hesse矩阵的近似计算,进而训练网络。
Platform: | Size: 19198 | Author: 刘慧 | Hits:

[Other resourceVC++BP

Description: 本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值. 一、网络训练 程序默认状态是样本训练状态,现将样本训练状态下的如何训练网络进行说明: 1.系统精度: 定义系统目标精度,根据需要定义网络训练误差精度.误差公式是对训练出网络的输出层节点和实际的网络输出结果求平方差的和. 最大训练次数: 默认为10000次,根据需要调整,如果到达最大训练次数网络还未能达到目标精度,程序退出. 3.步长: 默认为0.01,由于采用变步长算法,一般不需人工设置. 4.输入层数目: 人工神经网络的输入层神经元的节点数目. 5.隐含层数目: 人工神经网络的隐含层神经元的节点数目. 6.输出层数目: 人工神经网络的输出层神经元的节点数目. 7.训练算法: 强烈建议选取Levenberg-Marquardt算法,该算法经过测试比较稳定. 8.激活函数: 不同的网络激活函数表现的性能不同,可根据实际情况选择. 9.样本数据的处理: 由于程序没有实现归一化功能, 因此用来训练的样本数据首先要归一化后才能进行训练.
Platform: | Size: 344008 | Author: starboy_2nd | Hits:

[Other resourceNNBP

Description: 本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值。随代码还提供帮助文件,非常方便。-BP algorithm Demonstration Program, which Levenberg-Marquardt algorithm has practical value. With the code also provides help files, a very convenient.
Platform: | Size: 333044 | Author: 林瑞伦 | Hits:

[AI-NN-PRNNBP

Description: 本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值。随代码还提供帮助文件,非常方便。-BP algorithm Demonstration Program, which Levenberg-Marquardt algorithm has practical value. With the code also provides help files, a very convenient.
Platform: | Size: 332800 | Author: 林瑞伦 | Hits:

[AI-NN-PRbpnnet_154

Description: L-M算法。除了动量法(基于梯度下降的训练算法)外,学习率自适应调整策略是BP算法改进的另一种途径,它利用Levenberg-Marquardt优化方法,从而使得学习时间更短。其缺点是,对于复杂的问题,该方法需要很大的存储空间。 -L-M algorithm. In addition to momentum (based on the gradient descent algorithm for training), learning rate adaptive strategy is to improve the algorithm BP Another approach, which uses Levenberg-Marquardt optimization method, which makes learning time is even shorter. Its weakness is that the complex problems that the method requires a lot of storage space.
Platform: | Size: 1024 | Author: 辜小花 | Hits:

[AI-NN-PRBPmatlab

Description: matlab使用BP网络的例子,使用Levenberg Marquardt算法提高训练速度,效果不错-use Matlab BP example, the use of Levenberg Marquardt algorithm to improve training speed, good results
Platform: | Size: 4096 | Author: 汤泽世 | Hits:

[source in ebookdigital_recogonizer

Description: 神经网络进行手写数字识别: 本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值. 带有图形界面-neural network handwritten numeral recognition : this program is the BP algorithm Demonstration Program, The Levenberg-Marquardt algorithm is practical value. with a graphical interface
Platform: | Size: 133120 | Author: HK | Hits:

[File FormatNEURAL+NETWORK

Description: bp神经网络算法是解决最优化问题的先进算法之一,本论文讨论了神经网络中使用最为广泛的前馈神经网络。其网络权值学习算法中影响最大的就是误差反向传播算法(back-propagation简称BP算法)。BP算法存在局部极小点,收敛速度慢等缺点。基于优化理论的Levenberg-Marquardt算法忽略了二阶项。该文讨论当误差不为零或者不为线性函数即二阶项S(W)不能忽略时的Hesse矩阵的近似计算,进而训练网络。-bp neural network algorithm to solve optimization problems, one of the advanced algorithm, the paper discusses the neural network in the most widely used feed-forward neural network. Its network weights learning algorithm in the greatest impact is the error back-propagation algorithm (back-propagation algorithm referred to as BP). BP algorithm for the existence of local minimum points, such as the shortcomings of slow convergence. Optimization theory based on the Levenberg-Marquardt algorithm ignores the second-order item. In this paper, the discussion when the error is not zero or not that is second-order linear function of S (W) can not be ignored when the Hesse matrix of approximate calculation, and then training the network.
Platform: | Size: 19456 | Author: 刘慧 | Hits:

[Othermatmath_c

Description:
Platform: | Size: 7168 | Author: ywaly | Hits:

[AI-NN-PRVC++BP

Description: 本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值. 一、网络训练 程序默认状态是样本训练状态,现将样本训练状态下的如何训练网络进行说明: 1.系统精度: 定义系统目标精度,根据需要定义网络训练误差精度.误差公式是对训练出网络的输出层节点和实际的网络输出结果求平方差的和. 最大训练次数: 默认为10000次,根据需要调整,如果到达最大训练次数网络还未能达到目标精度,程序退出. 3.步长: 默认为0.01,由于采用变步长算法,一般不需人工设置. 4.输入层数目: 人工神经网络的输入层神经元的节点数目. 5.隐含层数目: 人工神经网络的隐含层神经元的节点数目. 6.输出层数目: 人工神经网络的输出层神经元的节点数目. 7.训练算法: 强烈建议选取Levenberg-Marquardt算法,该算法经过测试比较稳定. 8.激活函数: 不同的网络激活函数表现的性能不同,可根据实际情况选择. 9.样本数据的处理: 由于程序没有实现归一化功能, 因此用来训练的样本数据首先要归一化后才能进行训练.
Platform: | Size: 344064 | Author: starboy_2nd | Hits:

[AI-NN-PRbpwl

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 | Hits:

[AI-NN-PRNeuralnetworkstools

Description: 神经网络仿真工具,本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值.-Neural network simulation tool, this program is BP algorithm demo program in which the Levenberg-Marquardt algorithm has practical value.
Platform: | Size: 343040 | Author: zch | Hits:

[AI-NN-PRbpann

Description: bp神经网络, Levenberg-Maquardt算法-BPANN
Platform: | Size: 4096 | Author: hnu104_cc | Hits:

[matlabNNET

Description: BP-神经网络 The neural network is trained with the Levenberg-Marquardt algorithm. The activation functions can be either linear ( L ) or hyperbolic tangent ( H ).-Backpropagation neural network with one hidden layer for multivariate calibration. (Designed to model only one response y at a time)
Platform: | Size: 20480 | Author: 郭乐 | Hits:

[AI-NN-PRThe-instruction-of-NNBP-1.0

Description: NNBP 1.0使用说明,NNBP是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值-NNBP 1.0 instructions, NNBP is BP algorithm demo program, the Levenberg-Marquardt algorithm which has practical value
Platform: | Size: 5120 | Author: 李志坚 | Hits:

[AI-NN-PRtwodimapproximationbp

Description: 单输出函数Y=SIN(X)逼近问题的bp程序:假设网络结构为3--2--1,输入维数M,共N个样本,一般输入不算层,输出算层- 激活函数: hardlim---(0,1),hardlims---(-1,1),purelin,logsig---(0,1),tansig----(-1,1) softmax,poslin,radbas,satlin,satlins,tribas 训练算法: 1.traingd,traingdm,traingda(variable learning rate backpropagation),trainrp( resilient backpropagation ) 2.conjugate gradient (traincgf, traincgp, traincgb, trainscg), quasi-Newton (trainbfg, trainoss), and Levenberg-Marquardt (trainlm).
Platform: | Size: 2048 | Author: 刘老师 | Hits:

[Mathimatics-Numerical algorithmsBP_algorithm

Description: 本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值.-This program is BP algorithm demo program, in which the Levenberg-Marquardt algorithm has practical value.
Platform: | Size: 331776 | Author: 初光磊 | Hits:

[AI-NN-PRBP_Differ_Train

Description: BP神经网络算法用来拟合加噪信号,并以动量梯度下降算法和减少内存的Levenberg-Marquardt算法两种训练方法进行该实例下的性能对比-BP neural network algorithm used to fit the noise signal, and to reduce the momentum gradient algorithm and memory Levenberg-Marquardt algorithm two training methods to compare the performance of the example
Platform: | Size: 1024 | Author: 寻家军 | Hits:

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