搜索资源列表
Matlab-digital-based-recognition-
- 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, Mah
bayes
- 简单贝叶斯分类器,分别采用欧式距离和马氏距离实现三类分类-Simple Bayesian classifier
alzheimers_classifier
- 基于马氏分类器的阿兹海默氏症分类器,课程练习-Based on Mahalanobis classifier classifier of Alzheimer' s disease
colorseg2
- 对彩色图像进行分层,并且使用欧式距离和马氏距离作为辅助计算,效果很好。-Stratified, the color image and use the Euclidean distance and Mahalanobis distance as an auxiliary, the effect is very good.
flower
- 对花卉的数据集分别通过“五折法”、随机产生训练样本、欧式平方距离、绝对值距离、契比雪夫距离和马氏距离进行数据集的识别。-Data sets, respectively, for flowers through the " half of Law" , randomly generated training samples, European squared distance, absolute distance, Chebyshev distance and Mahalanobi
mahala2
- 利用马氏可分性度量函数绝对子集惊醒可分能力的排序-Separability measure function using the Markov absolutely awakened separable subset sorting capabilities
Markov-Decision-Process-matlab
- 马氏过程的应用很广, 机器人路径计划, 自动飞行器导航,多目标跟踪, 电梯计划, 网络交换和路由, 银行客户保有等等。-Application of Markov process is broad, robot path plan, automatic vehicle navigation, multi-target tracking, lift plans, network switching and routing, bank customers to maintain and so on.
robust-MD-estimation
- 稳健马氏距离的计算,并与一般马氏距离比较,主要应用于模式识别等领域-robust MD estimation
Example
- 马氏距离聚类分析案例,通过分析光谱数据,对样本进行训练并执行新的样本分类-Mahalanobis distance clustering analysis of case
MahalanobisDistanceDiscrimination
- 马氏距离判别(MahalanobisDistanceDiscrimination)的演示过程,求均值向量,协方差矩阵及线形判别函数-Mahalanobis distance criterion (MahalanobisDistanceDiscrimina tion) demonstration process for the mean and covariance matrix and linear discriminant function
example
- 马尔可夫链的小例子,希望对初学者了解马氏链及其应用有帮助。-Matlab code of markov chain, hope it will be helpful to you
melm-learn-machine
- 基于马氏椭球学习机的监督野点探测;属于极限学习机elm算法在模式识别, 智能信息处理技术方面的应用论文:针对ssdd、melm、sodmelm算法比较-Supervised outlier detection based on Mahalanobis ellipsoid learning machine belong extreme learning machine algorithm elm papers in pattern recognition, intelligent informa
Markov-chain-model
- 介绍了马氏链模型的原理、方法和运用,并有详细的事例进行了说明。-Introduces the principle, method and application of Markov chain model, and detailed examples are illustrated.
Markov-series
- 随机生成满足马氏性P-III型分布和对数正态分布序列-The generation of Markov series that have a P-III disrtibution or three parameters LN distribution
classifier
- 各种分类器的源码,有注释和功能描述,马氏,贝叶斯,最大似然等-Various classifier source, there are notes and functional descr iption
Markov-Chain
- 基于马氏链的股指期货合约指数的预测。转移频数 概率矩阵 平稳分布方程组 方程组的解 平均返回时间-Prediction of Stock Index Futures Price Based on Markov Chain Markov Chain transition probability matrix stationary distribution.
gibbs
- Gibbs Sampling 这个绝妙的想法在1953年被 Metropolis想到了,为了研究粒子系统的平稳性质, Metropolis 考虑了物理学中常见的波尔兹曼分布的采样问题,首次提出了基于马氏链的蒙特卡罗方法,即Metropolis算法,并在最早的计算机上编程实现。Metropolis 算法是首个普适的采样方法,并启发了一系列 MCMC方法,所以人们把它视为随机模拟技术腾飞的起点。 Metropolis的这篇论文被收录在《统计学中的重大突破》中, Metropolis算法也被遴选为二十
md_gen
- 计算马氏距离,datasample是基准总体,行为特征值,列为各样本值,如5x1000,testdata是要进行计算的特征向量,MD为计算出的马氏距离-Mahalanobis distance calculation, datasample benchmark overall behavior eigenvalues, as the value of each sample, such as 5x1000, testdata is necessary to calculate the featu
ASM-2.2.1
- 对模型特征点周围的纹理信息进行采样,对比图像和模型训练集的纹理,找到纹理最接近的点即认为是特征点。作者这里比较纹理的工具是马氏距离。为了提高搜索的效率,作者还提到了多分辨率搜索周围像素纹理,对于粗糙的尺度,搜索范围大,对于细致的尺度,进行细致的搜索,提高了匹配的效率。-The texture information model feature points around the sampling, texture contrast image and model train sets, find
bhattacharyya-distance_
- 是在数学建模中用到的计算马氏距离的好的方法,对于初学者很有用-It is a good method of calculating Mahalanobis distance in the mathematical modeling used, very useful for beginners