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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
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神经网络感知器学习规则：Delta学习规则。采用Delta学习规则，进行权值调整，阈值变换函数采用双极性连续函数。程序简单易懂，希望对大家有所帮助！-Neural network perceptron learning rule: Delta learning rule. Delta learning rule used to carry out the right to adjust the value of the threshold bipolar transfer function us
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ga优化神经网权值&阈值程序。为了方便，我把几个matlab的程序都放在txt文件里，使用时，对照把txt内容复制进matlab即可-ga optimization neural network weights & threshold procedures. For convenience, I have several matlab programs on the txt file, use, control the content of the txt you copied into
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ga优化神经网权值&阈值程序。
优化的基本原理和过程很多论文可以查到，在此不必赘述我就把用gaot5的小程序贴在下面吧，也是y=1/x-ga optimization neural network weights & threshold procedures. Optimization of the basic principles and processes can be found in many papers, do not have to go into details he
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用遗传算法优化BP神经网络的权值及其阀值-Using genetic algorithm optimization BP neural network weights and threshold
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用MATLAB实现二层bp神经网络的计算。可以改变阈值和权值以改进算法，并可以将该方法推广到多层网络。-Using MATLAB to achieve the second floor bp neural network computing. Can change the threshold value and weight to improve the algorithm and the method can be extended to the multi-layer network.
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这是一个采用遗传算法优化bp神经网络权值阈值的MATLAB程序-This is a genetic algorithm to optimize neural network weights bp threshold MATLAB program
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关于BP神经网络的程序代码，包括阈值和权值的调整，现在在石油开发测井应用非常广泛-Regarding the BP neural network program code, include threshold value and the adjustment of oil well logging, now is used extensively
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网络结构、初始连接权值和阈值的选择对网络训练的影响很大，但是又无法准确获得，针对这些特点可以采用遗传算法对神经网络进行优化-Network structure, initial connection weights and threshold selection a great impact on the network training, but it is impossible to accurately obtain, these features can be used for the
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基于遗传算法和BP神经网络控制倒立摆的程序，用遗传算法优化神经网络权值阈值以达到更好的控制效果-Based on genetic algorithm and BP neural network control procedures for the inverted pendulum, with a genetic algorithm neural network weight threshold in order to achieve better control performance
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该算法也是人工神经网络理论中的线性阈值神经元的学习算法-The algorithm of artificial neural network theory is the linear threshold learning algorithm of neural
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构建BP神经网络，源码。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hide layer)和输出层(output layer)。-BP neural network to build, source. BP network can learn and store a lot of input- out
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网络将输入模式加权求和、与门限比较、再进行非线性运算，得到网络的输出-The network will be weighted sum input mode, compared with the threshold, then a nonlinear operator to get the output of the network
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使用遗传算法对径向基神经网络进行阈值的优化-Threshold optimization using a genetic algorithm for radial basis function neural network
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带阈值的三层BP神经网络，包括输入层，隐层，输出层。实现sin函数功能。-The BP neural network, including input layer, hidden layer and output layer, with a threshold value,can realize the sin() function.
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运行平台MATLAB，基于BP神经网络的语音分类，含权值与阈值的计算-Operating platform of MATLAB, the BP neural network-based voice classification, with the right values and the threshold calculation
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bp神经网络阈值和权值设定，自己设定，再也不需要用rands默认设定-BP neural network threshold and weight settings, set their own, no longer need to use the default setting rands
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3隐层的bp神经网络，有详细的注释，各隐层的权值调整、输出层阈值调整，学习样本输出层至隐层一般化误差-3 bp neural network hidden layer, there are detailed notes, each hidden layer weight adjustment, the output layer threshold adjustment, learning sample output layer to the hidden layer generalization
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采用最先进的殖民竞争算法Imperialist competition algorithm优化BP神经网络的初始权值、阈值，进行风电功率预测，带数据和实例，ica为主程序-Using the most advanced colonial competitive algorithm Imperialist competition algorithm to optimize the initial weights of BP neural network, threshold, carry wind
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利用Maltab脚本M语言，使用GA遗传算法优化BP神经网络阈值，文件包括：ga_bp和gaot工具箱，首先在maltab中利用setpath设置加载gaot工具箱，然后在ga_bp文件夹下运行！(Using Maltab scr ipt M language, we use GA genetic algorithm to optimize BP neural network threshold. The files include ga_bp and GAOT toolbox. First,
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