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產生k個d維的常態分布樣本，產生某個事前機率為P(wi)的常態分布的discriminant
function，計算任兩點間的Euclidean distance及Mahalanobis distance
-Generated k-d-dimensional normal distribution of samples to generate a prior probability P (wi) of the normal distribution of the discriminan
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基于欧拉-熵向量的图像检索,相似度可用马氏距离-Based on Euler- entropy vector image retrieval, similarity can be used Mahalanobis distance
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Mahalanobis距離是一個可以準確找出資料分布上面極端值(Outliers)的統計方法,使用線性迴歸的概念,也就是說他使用的是共變數矩陣以及該資料分布的平均數來找尋極端值的產生,而可以讓一群資料系統具有穩健性(Robust),去除不必要的雜訊訊息,這邊拿前面共變數矩陣的資料為例,並且新增了兩個點座標向量來做Mahalanobis距離的比較-Mahalanobis distance is the information that can accurately identify the dis
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使用Matlab基于直方图、欧式距离和马氏距离实现视频镜头分割-This project takes a video as input and converts it into frames. From the numerous frames it identifies only a few number of frames which are the key frames. Key frames are identifies by implementing Histogram analysis
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Isodata iterative self-organizing data analysis, Energy spectrum analysis and calculation, Using matlab to calculate the Mahalanobis distance for the image.
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A complete set of brothers, Correlation analysis process matlab method, Using matlab to calculate the Mahalanobis distance for the image.
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Using matlab to calculate the Mahalanobis distance for the image, It uses a pulse of consumer law, matlab wavelet analysis program.
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