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主分量分析(PCA ) 是统计学中分析数据的一种有效的方法, 可以将数据从高维数据空间变换到低维特征空间, 因而
可以用于数据的特征提取及压缩等方面。在该文的形状识别系统中, 用PCA 法提取图像的形状特征, 能够较好地满足识别
层的输入要求。在识别层研究了3 种识别方法: 最近邻法则、BP 网络及协同神经网络方法, 均取得了满意的实验效果。-Principal component analysis (PCA) is a statistical analysis of data in a
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matlab
用PCA方法对图像进行压缩、还原-PCA method using matlab image compression, restore
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PCA for image compression, Sanger s algorithm implemented with neural networks
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the code conducts the image compression of the gray scale image up to 90 using 4 algos fft wavelet pca and cosine transform-the code conducts the image compression of the gray scale image up to 90 using 4 algos fft wavelet pca and cosine transform
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Principal components analysis is one of a family of
techniques for taking high-dimensional data, and using the
dependencies between the variables to represent it in a more
tractable, lower-dimensional form, without losing too much
information. PC
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