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主元分析 (Principal Component Analysis, PCA) 又叫：Karhunen-Loeve变换
(KLT)、Hotelling变换。
假设已经从图象已经缩放为N*M大小。
m幅N*M大小的图象Xi作为n*1列向量看待-PCA (Principal Component Analysis, PCA) also known as: Karhunen-Loeve Transform (KLT), Hotelling transform.
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Function to compute the Karhunen-Loeve Transform (KLT) on an ensemble of 1-D signals,
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基于Fourier-Bessel展开和Karhunen-Loeve变换的语音变 换基于Fourier-Bessel展开和Karhunen-Loeve变换的语音变换-Based on Fourier-Bessel expansion and Karhunen-Loeve transform based on Fourier-Bessel transform voice expansion and Karhunen-Loeve transform for voice conversion
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compression using karhunen loeve transform
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对“data4.m”数据，采用三种K-L变换，分别提取2个特征。-The "data4.m" data, using the three KL transform, two features were extracted.
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给出图像处理中应用比较广泛的三种方法：Karhunen－Loeve变换-离散余弦变换-小波变换在图像处理中的比较，供参考-Given the image processing application in a wide range of three methods: Karhunen-Loeve transform- discrete cosine transform- wavelet transform in image processing, comparison and for refer
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Simple matrix algebra C++ library.
Implements such a useful tools like a:
- Linear equation solving via QT decomposition
- Singular value decomposition
- Karhunen-Loeve transform
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Karhunen—Loeve变换及其图像中的应用(Karhunen - Loeve transform and its applications in images)
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小波变换 KLT变换 图像处理 小波变换和KLT变换的matlab实现(Matlab implementation of wavelet transform, KLT transform, image processing, wavelet transform and KLT transform)
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Iris数据集，计算协方差矩阵和相关系数矩阵和kl变换(The goal of this programming experiment is to:
Calculate the covariance matrix and the correlation coefficient matrix of the Iris data set. Perform the Karhunen-Loeve transform on this data set.)
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