Description: 一种新的计算马氏距离的算法，算法采用二次协方差矩阵操作，进而使距离考加入相对性因素。-a new Mahalanobis distance calculation algorithm, the algorithm using quadratic covariance matrix operations, thereby enabling the relative distance to take factors. Platform: |
Size: 1024 |
Author:bodiz2002 |
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Description: 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 discriminant function, calculated between any two points in Euclidean distance and Mahalanobis distance Platform: |
Size: 38912 |
Author:amy |
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Description: 本文针对SLAM算法中数据关联过程，提出了一种简单易行的改进方法，将欧氏距离与马氏距离结合用于数据关联。算法不必计算地图所有特征与所有量测之间的马氏距离，而是首先利用相对简单的欧氏距离计算缩小了待关联特征的搜寻范围。利用人工合成数据的仿真结果表明，改进后的数据关联方法可以大幅减少系统计算量，提高关联效率，且不会造成错误关联的增加。-This article SLAM algorithm for data association process, a simple method to Euclidean distance combined with the Mahalanobis distance for data association. Algorithms do not have to calculate all the characteristics of the map with all measurements between the Mahalanobis distance, but the first to use a relatively simple calculation of Euclidean distance to be associated characteristics of narrowing the search. The use of synthetic data simulation results show that the improved methods of data association can significantly reduce the system to calculate the volume and improve the efficiency of association, and will not lead to errors associated with an increase. Platform: |
Size: 13312 |
Author:liancb |
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Description: 用matlab实现的几种模式识别的方法，有切比雪夫距离法，马氏距离法，欧氏距离法。而且每种方法都给出了多种编程-Matlab achieved using several methods of pattern recognition, there are Chebyshev distance, Mahalanobis distance method, Euclidean distance method. But each method are given a variety of programming Platform: |
Size: 82944 |
Author:mr yao |
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Description: This package contains Matlab m-files for learning finite Gaussian mixtures from sample data and performing data classification with Mahalanobis distance or Bayesian classifiers. Each class in training set is learned individually with one of the three variations of the Expectation Maximization algorithm: the basic EM algorithm with covariance fixing, the Figueiredo-Jain clustering algorithm and the greedy EM algorithm.
The basic EM and FJ algorithms can handle complex valued data directly, the greedy EM algorithm cannot.
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Size: 20480 |
Author:李 |
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Description: 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 distribution of the above extreme values (Outliers) statistical methods, the concept of using a linear regression, meaning that he used the covariance matrix and the distribution of the information to find the extreme values of the average production of , but can allow a group of information systems with the robustness (Robust), removing unnecessary noise message here get in front of the data covariance matrix, for example, and added two points, coordinates of vectors to do comparison of Mahalanobis distance Platform: |
Size: 1024 |
Author:nip |
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Description: 马氏距离的仿射不变性删除误匹配特征点
对，据此可求取2幅源图像间的仿射变换参数-Mahalanobis distance of the affine invariant features remove the false matching points
Yes, according to the source to obtain two parameter affine transformation between images Platform: |
Size: 1024 |
Author:yimeng |
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Description: 基于图像检索的matlab代码，基于内容的图像检索中的一些关键环节：特征提取：颜色直方图；纹理特征等 相似度：马氏距离，欧氏距离等 相关反馈：机器学习方法，如SVM，神经网络等 检索与分类：两个很相似的样本距离很小，虽然两个不相似的样本距离未必很大-content-based image retrieval of some of the key issues : Feature Extraction : color histogram Texture characteristics of similarity : Mahalanobis distance, the Euclidean distance relevance feedback : machine learning methods, such as SVM. Neural network search and classification : two very similar samples from the small, although the two are similar to the samples may not be much distance Platform: |
Size: 164864 |
Author:EmilyFu |
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Description: 这6个程序可用于0—9的数字识别，算法包括：基于类中心的欧式距离法、马氏距离法、夹角余弦距离法
、二值化的夹角余弦距离法、二值化的Tanimoto测度法和增量校正算法，均为基于matlab软件编写的程序。学会了这几个算法，可以在这些程序的基础上进行扩展，对三维模型识别算法的编程有一定的帮助。-6 program can be used 0-9 digit recognition, algorithms include: class center Euclidean distance, Mahalanobis distance method, the cosine of the angle distance method, the cosine of the angle distance method binarization, binary of Tanimoto Measure Method and incremental correction algorithms are written based on matlab software program. Learned these algorithms can be extended on the basis of these procedures, programming algorithm of the three-dimensional model to identify some help. Platform: |
Size: 3072 |
Author:柏芝 |
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Description: There are detailed notes, Code, there are very complete notes and explanations Using matlab to calculate the Mahalanobis distance for the image. Platform: |
Size: 6144 |
Author:feiloujougang
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Description: For feature reduction, feature fusion, correlation analysis, Pisarenko harmonic decomposition algorithm, Using matlab to calculate the Mahalanobis distance for the image. Platform: |
Size: 5120 |
Author:ipixxpg
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Description: Using matlab to calculate the Mahalanobis distance for the image, Prediction Error Method for Parameter Identification - the idea of relaxation, You can achieve data classification and regression pattern recognition. Platform: |
Size: 6144 |
Author:mengjeilangtiu
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Description: For beginners with a reference value, Channelized receiver based on multi-phase structure, Using matlab to calculate the Mahalanobis distance for the image. Platform: |
Size: 6144 |
Author:nengqeisui
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Description: Using matlab to calculate the Mahalanobis distance for the image, Three-phase photovoltaic inverter and network simulation, Data packet transfer source program. Platform: |
Size: 60416 |
Author:bingnunneng
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