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Description: L-M算法(BP的一种改进算法)应用实例-L-M algorithm (BP an improved algorithm) Application
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Size: 1024 |
Author: 胡刚 |
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Description: 一个原始的BP网络的M程序-a primitive network BP M procedures
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Size: 1024 |
Author: 张旭 |
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Description: 基于C开发的三个隐层神经网络，输出权值、阈值文件，训练样本文件，提供如下函数：1）初始化权、阈值子程序；2）第m个学习样本输入子程序；3）第m个样本教师信号子程序；4）隐层各单元输入、输出值子程序；5）输出层各单元输入、输出值子程序；6）输出层至隐层的一般化误差子程序；7）隐层至输入层的一般化误差子程序；8）输出层至第三隐层的权值调整、输出层阈值调整计算子程序；9）第三隐层至第二隐层的权值调整、第三隐层阈值调整计算子程序；10）第二隐层至第一隐层的权值调整、第二隐层阈值调整计算子程序；11）第一隐层至输入层的权值调整、第一隐层阈值调整计算子程序；12）N个样本的全局误差计算子程序。-C development based on the three hidden layer neural network, the output weights, threshold documents, training sample documents, for the following functions : a) initialization, the threshold subroutine; 2) m learning samples imported subroutine; 3) m samples teachers signal Subroutine ; 4) hidden layer of the module input and output value subroutine; 5) the output layer of the module input and output value subroutine; 6) the output layer to the hidden layer subroutine error of generalization; 7) hidden layer to the input layer subroutine error of generalization; 8) the output layer to the third hidden layer Weight adjustment, the output layer threshold adjustment routines; 9) 3rd hidden layer to the second hidden layer weights adjustment, the third hidden layer threshold adjustment routi
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Size: 11264 |
Author: 李洋 |
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Description: 应用bp神经网络实现了函数逼近,并用matlab程序实现了整个过程-Bp neural network applications realize the function approximation, and the procedures used matlab realize the whole process
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Size: 1024 |
Author: kingkof |
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Description: 基于BP神经网络的 参数自学习控制
（1）确定BP网络的结构，即确定输入层节点数M和隐含层节点数Q，并给出各层加权系数的初值 和 ，选定学习速率 和惯性系数 ，此时k=1；
（2）采样得到rin(k)和yout(k)，计算该时刻误差error(k)=rin(k)-yout(k)；
（3）计算神经网络NN各层神经元的输入、输出，NN输出层的输出即为PID控制器的三个可调参数 ， ， ；
（4）根据(3.34)计算PID控制器的输出u(k)；
（5）进行神经网络学习，在线调整加权系数 和 ，实现PID控制参数的自适应调整；
（6）置k=k+1，返回（1）。
-Based on the parameters of BP neural network self-learning control (1) to determine the structure of BP network, that is, determine the input layer nodes M and hidden layer nodes Q, and gives all levels of the initial value and the weighted coefficient, the selected learning rate and inertia coefficient, when k = 1 (2) sample has been rin (k) and the yout (k), calculate the moment of error error (k) = rin (k)-yout (k) (3) calculation of neural network NN all floors of the neurons in input and output, NN output layer is the output of PID controller for the three adjustable parameters,, (4) According to (3.34) Calculation of PID controller output u (k) (5) to carry out neural network learning, on-line adjustment of the weighted coefficient and, realize the adaptive PID control parameters adjust (6) purchase k = k+ 1, return (1).
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Size: 1024 |
Author: dake |
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Description: ”BP.m“文件是BP神经网络整个模型的源程序；
“train.fig”是训练时最后得到的图片；
“程序运行的人口数量原始数据.fig”是预测结果绘制的图；
“程序运行时matlab命令窗口的内容.txt”是运行程序是在matlab命令窗口显示的东西；
“程序运行完产生的数据.mat”是程序运行完毕产生的数据。
.bmp文件和.fig文件一样
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Size: 36864 |
Author: Dong Liang |
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Description: BP神经网络的源代码,是用MATLA的.M文件写的,希望对大家有帮助-BP neural network source code, is MATLA of. M document written, in the hope that everyone has to help
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Size: 3072 |
Author: |
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Description: MRF能量解算中的的BP算法，速度快，效果很好！-MRF energy solver of the BP algorithm, fast, good effect!
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Size: 284672 |
Author: li |
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Description: 采用动量梯度下降算法训练BP网络，采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络-Gradient descent algorithm using momentum BP network training, using two training methods, namely, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to facilitate the training of BP network
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Size: 3072 |
Author: 闫薇 |
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Description: 一种利用神经网络计算L-M算法的程序。里面还有其他的算法可以参考-A neural network algorithm for calculating the LM procedure. There are other algorithms which can refer to
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Size: 333824 |
Author: wolf |
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Description: 一个非常不错的BP算法程序，这是一个名为bp.m的文件，对于理解BP算法会很有帮助。-The BP algorithm is a very good program, it is a named bp.m file would be helpful for understanding the BP algorithm.
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Size: 2048 |
Author: 侯杰 |
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Description: L-M,BP网络算法，用matlab语言编译-LM, BP network algorithm with matlab compiler
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Size: 1024 |
Author: 方芳 |
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Description: 神经网络BP算法的实现和两个小例子,其中包括两个.m文件和一个说明文档-Implementation of neural network BP algorithm and two small examples, including two. M file and a documentation
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Size: 94208 |
Author: hujuan123 |
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Description: BP算法源程序，可改动隐含节点数，一个简单的例子。-BP algorithm source code can be changed hidden nodes, a simple example.
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Size: 1024 |
Author: 张晨 |
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Description: 利用MATLAB的自带工具箱函数实现了北京2009年12个月份气温、降水和气压的走势预测，且效果比较好。
BP神经网络
Bp.m BP神经网络MATLAB程序
bp_ds.xls 训练集输入
bp_nds.xls 训练集输出（目标训练集）
bp_td.xls 测试集输入
bp_ntd.xls 测试集输出（目标测试集）
BP神经网络预测天气值.doc 论文
-Use of MATLAB toolbox to realize the function of the cabin Beijing 2009 12 months the temperature, precipitation and pressure trend projections, and the effect is better.
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Size: 15360 |
Author: 电子develop |
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Description: BP神经网络异或问题 使用说明：打开文件夹中的BP.m文件，在matlab中运行此m文件，即可在command window中得出结果。压缩包内附说明文件-XOR problem of the BP neural network for use: Open the folder in BP.m file, run this m file in matlab to the outcome of the command window. Compression package containing the documentation
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Size: 22528 |
Author: 王浩 |
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Description: 径向基神经网络训练matlab程序,并画出预测数据和原数据的对比图。-RBF-BP neural network algorithm Matlab code, the procedures under the trained network , be mean square error, paint and forecast data and the original data in contrast to Fig. Hope useful
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Size: 3072 |
Author: qj |
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Description: BP神经网络代码，使用LM算法（高斯牛顿法的改进，具有很好的鲁棒性）-BP neural network code, use the LM algorithm (modified Gauss-Newton method has good robustness)
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Size: 1024 |
Author: xufeng |
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Description: 在工程应用中 经常会遇到一些复杂的非线性系统, 这些系统状态方程复杂, 难以 用数学方
法准确建模。 在这种情况下, 可以 建立 BP 神 经网 络表达这些 非 线 性系 统。 该方法把未 知 系
统看成是一个黑箱, 首先用 系 统 输入输出 数据 训 练 BP 神 经网 络, 使网 络能 够表达该未 知 函
数, 然后就可以 用训练好的 BP 神经网络预测系统输出 。
本章拟合的非线性函 数为
y = x1^2+x2^2.
。-In engineering applications often encounter some complex nonlinear systems, which complicated the equation of state, can not be accurately modeled mathematically. In this case, BP neural network can be established to express these nonlinear systems. The method of the unknown system as a black box, the first input and output data with systematic training BP neural network, the network can express the unknown function, then you can use the trained BP neural network forecasting system output. Chapter for fitting non-linear function y = x1 ^ 2+x2 ^ 2..
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Size: 1024 |
Author: 安茹 |
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Description: BP神经网络建模归一化数据处理神经网络训练分类以及遗传算法优化的BP神经网络函数拟合(BP neural network modeling normalized data processing neural network training classification and genetic algorithm optimization BP neural network function fitting)
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Size: 1024 |
Author: wwhh
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