搜索资源列表
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C-均值聚类
BP神经网络信号分析与处理方法，对模拟产生的数据样本进行训-C-means clustering analysis and BP neural network signal processing method, the simulated data generated training samples
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k均值聚类算法,初始随机给定k个簇中心，根据邻近原则，把待分类的样本点分到各个簇。-k-means clustering algorithm,which is applied in RBF neural network.
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用自组织特征映射神经网络对Iris数据集进行分类，我用神经网络工具箱编写了个简单的程序，实现iris的分类。-Using self-organizing feature map neural network examples of clustering Iris data set classification, I use neural network toolbox to write a simple program, realize the classification of Iris.
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基于聚类的径向基神经网络的设计算法，采用的是K均值聚类。实现函数拟合！-The design algorithm of radial basis function neural network based on clustering, using the K mean clustering. Realize the function fitting!
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GLVQ neural network, this method is suitable for the two classification results of data processing
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神经网络聚类的matlab实现，内含多个文件-Matlab neural network clustering to achieve
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graynet_prediction algorithm文件夹为灰色神经网络的预测算法—订单需求预测
kohonen_cluster文件夹为网络的聚类算法—网络入侵聚类-graynet_prediction algorithm folder is gray neural network prediction algorithm- order demand forecast
kohonen_cluster folder is clustering algorithm network-
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这是一个关于Kohonen神经网络的小程序，主要实现了利用神经网络进行聚类的功能，经测试具有良好效果-This is a small program on Kohonen neural network, the main achievement of the neural network clustering feature has been tested with good results
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关于神经网络控制，仿真效果非常好，基于欧几里得距离的聚类分析。- On neural network control, Simulation of the effect is very good, Clustering analysis based on Euclidean distance.
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基于欧几里得距离的聚类分析，关于神经网络控制，用MATLAB实现动态聚类或迭代自组织数据分析。- Clustering analysis based on Euclidean distance, On neural network control, Using MATLAB dynamic clustering or iterative self-organizing data analysis.
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基于人工神经网络的常用数字信号调制，可实现对二维数据的聚类，加入重复控制。- The commonly used digital signal modulation based on artificial neural network, Can realize the two-dimensional data clustering, Join repetitive control.
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基于欧几里得距离的聚类分析，BP神经网络的整个训练过程,详细画出了时域和频域的相关图。- Clustering analysis based on Euclidean distance, The entire training process BP neural network, Correlation diagram shown in detail the time domain and frequency domain.
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实现用神经网络的聚类问题，采用了PSO进行优化，引入了浮动质心的概念-Implement clustering and neural network
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BP神经网络用于函数拟合与模式识别，用MATLAB实现动态聚类或迭代自组织数据分析，主同步信号PSS在时域上的相关仿真。- BP neural network function fitting and pattern recognition, Using MATLAB dynamic clustering or iterative self-organizing data analysis, PSS primary synchronization signal in the time domai
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isodata 迭代自组织的数据分析，可实现对二维数据的聚类，关于神经网络控制。- Isodata iterative self-organizing data analysis, Can realize the two-dimensional data clustering, On neural network control.
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基于欧几里得距离的聚类分析，通过虚拟阵元进行DOA估计，BP神经网络用于函数拟合与模式识别。- Clustering analysis based on Euclidean distance, Conducted through virtual array DOA estimation, BP neural network function fitting and pattern recognition.
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可实现对二维数据的聚类，基于人工神经网络的常用数字信号调制，阵列信号处理的高分辨率估计。- Can realize the two-dimensional data clustering, The commonly used digital signal modulation based on artificial neural network, High-resolution array signal processing estimates.
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BP神经网络的整个训练过程,分数阶傅里叶变换计算方面,可实现对二维数据的聚类。- The entire training process BP neural network, Fractional Fourier transform computing, Can realize the two-dimensional data clustering.
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是一种双隐层反向传播神经网络，基于K均值的PSO聚类算法,构成不同频率的调制信号。- Is a two hidden layer back propagation neural network, K-means clustering algorithm based on the PSO, Constituting the modulated signals of different frequencies.
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MinkowskiMethod算法 ,是一种双隐层反向传播神经网络，用MATLAB实现动态聚类或迭代自组织数据分析。- MinkowskiMethod algorithm, Is a two hidden layer back propagation neural network, Using MATLAB dynamic clustering or iterative self-organizing data analysis.
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