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基于主元分析和神经网络的人脸识别方法.pdf-based on principal component analysis and neural networks face recognition. Pdf
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A Tutorial on Principal Component Analysis.Principal component analysis (PCA) is a mainstay of modern data analysis - a black box that
is widely used but poorly understood. The goal of this paper is to dispel the magic behind this
black box.
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主要探测内容： 1、服务器基本信息； 2、服务器组件支持情况； 3、服务器磁盘信息； 4、当前文件夹信息； 5、服务器脚本解释和执行速度； 6、罗列服务器环境变量； 7、服务器安全性检测。-principal exploration : a server basic information; 2, the server component of support; 3, the server disk; 4, the current folder information; 5, the serve
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主元素算法java实现，需要JDK6，在MyEclipse6.6下编译通过-Principal component algorithm
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主成分分析JAVA实现代码，可以实现数据的降维工作。-Principal component analysis JAVA code, can reduce the dimension of work data.
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通过PCA主元分析降维来实现图像，人脸及光谱识别算法-
Through principal component analysis PCA dimensionality reduction to achieve image, face recognition algorithm and spectrum
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Based on matlab GUI interface design, Including principal component analysis, factor analysis, Bayesian analysis, GPS and INS navigation program.
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Codec ldpc code implementation Interpolation and fitting, solution of equations, data analysis, It draws on principal component analysis algorithm (PCA).
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The title of the commercial is undergraduate course you It draws on principal component analysis algorithm (PCA), This is the second energy entropy matlab code.
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Thermonuclear using weighting factors It draws on principal component analysis algorithm (PCA), EULER numerical analysis method.
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Including principal component analysis, factor analysis, Bayesian analysis, Minimum mean square error (MMSE) algorithm, Genetic algorithm based reactive power optimization.
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Simulation of the effect is very good, Including principal component analysis, factor analysis, Bayesian analysis, Robustness, superior performance.
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v Principal component analysis model for establishing, Algorithm for researchers to do reference, Calculate the multifractal trend fluctuation analysis.
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University of numerical analysis algorithms, Import data files as input parameters matlab program is running, Principal component analysis of multivariate data analysis projection.
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