搜索资源列表
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将pca和elman神经网络结合起来，找到了主要的变量-The PCA and the Elman neural network to combine to find the main variables
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先运用pca找到主要的影响变量，然后用rbf神经网络建模-First use PCA to find the impact of major variables, and then use the rbf neural network modeling
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用基于Oja准则的PCA神经网络方法实现MUSIC算法，完成DOA估计 -Oja-based guidelines for the PCA neural network method MUSIC algorithm, the completion of the estimated DOA
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基于matlab 的神经网络计算，解压缩后直接运行
-Matlab neural network-based computing, unzip it and directly run
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1.BP神经网络进行模式识别
2.用BP网络对非线性系统进行辨识
3.一个神经网络PID控制器
4.图像处理的PCA算法
5.图像处理的穷举算法-1.BP neural network pattern recognition 2. Using BP network identification of nonlinear systems 3. A neural network PID controller 4. The PCA algorithm for image process
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One of Biometrics fields is face recognition & face expression recognition ...
1- In face recognition .. we need to design authentication program by training a neural network ,there are two source codes..one of them is based on Discrete Wavelet Tr
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LVQ神经网络的预测——人脸识别 LVQ神经网络的预测——人脸识别-LVQ neural network forecasting- LVQ neural network prediction Face- Face Recognition
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涉及的技术有：小波分析，尺度缩减模型（PCA,LDA,ICA），人工神经网络（ANN），-Techniques involved are: wavelet analysis, scaling down model (PCA, LDA, ICA), artificial neural network (ANN),
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PCA neural network Matlab code
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matlab下采用som神经网络算法进行100个人脸识别，可扩展性强。-som neural network using matlab under 100 face recognition algorithm, scalability.
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基于PCA-BP神经网络的接地网故障诊断算法-Ground Fault diagnosis algorithm PCA-BP neural network
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在建模前先将数据利用PCA进行降维，将降维后的数据作为BP神经网络的输入因子，对数据进行拟合。-Before the first data modeling use PCA dimensionality reduction, the reduced dimensionality of the data as the input factor BP neural network, the data fitting.
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又提供一基于生理的情感神经网络，包含杏仁体，丘脑，视觉神经等重要元素，可用于分类与预测，性能优越于SVM，BP-The use of neural network based on emotional physiology, contains important elements of the amygdala, thalamus, optic nerve, etc., can be used for classification and prediction, superior perform
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这是基于MATLAB 的神经网络训练算法的源程序，希望对大家有用-This is based on the MATLAB neural network training algorithm source, we hope to be useful
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应用主成分分析对数据降维，将得到的数据用于概率神经网络训练，进行模式识别。对于一组新数据，先计算主成分得分，再输入训练好的概率神经网络，就会得到识别结果，即改组数据属于何种类别。-Principal component analysis of the data reduction, data will be obtained for the probabilistic neural network training, pattern recognition. For a new set of d
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PCA和BP神经网络结合，适用于人脸识别中-PCA and BP neural network for face recognition
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The pca method was used for the classification of BP neural network
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神经网络BP算法，PCA算法以及PNN算法(Neural network BP algorithm and PNN algorithm)
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一种特征提取方法：结合主元分析(PCA)和核主元分析（KPCA）的前馈神经网络（FNN）(A feature extraction method: the feedforward neural network (FNN) combined with principal component analysis (PCA) and kernel principal component analysis (KPCA))
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PCA Neural Network System
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