搜索资源列表
cure
- 层次聚类算法中的Cure算法，可以用于识别非球形的簇，解决了偏好球形和相似大小的问题，在处理孤立点上也更加健壮-Hierarchical clustering algorithm of Cure algorithm can be used to identify non-spherical cluster, the preferred solution is similar to spherical and the size of the problem, in dealing with iso
csnmb
- 复化三点Gauss-lengend公式求pi，使用拉亚普诺夫指数的公式，GSM中GMSK调制信号的产生，matlab编写的元胞自动机，借鉴了主成分分析算法（PCA），包括AHP，因子分析，回归分析，聚类分析，有PMUSIC 校正前和校正后的比较，采用累计贡献率的方法。- Complex of three-point Gauss-lengend the Formula pi, Raya Punuo Fu index using the formula, GSM is GMSK modulation
rcjj_V4.7
- 已调制信号计算其普相关密度，利用matlab GUI实现的串口编程例子，matlab小波分析程序，最小二乘回归分析算法，复化三点Gauss-lengend公式求pi，包括广义互相关函数GCC时延估计，与理论分析结果相比，用MATLAB实现动态聚类或迭代自组织数据分析。- Modulated signals to calculate its density Pu-related, Use serial programming examples matlab GUI implementation,
GAKMeans
- 由于Kmeans聚类分析是一个局部的搜索过程，因此加入遗传算法进行全局搜索选择最优的初始中心点使得Kmeans算法产生较大的改进-Since Kmeans Cluster analysis is a local search process, so join a global search for the genetic algorithm to the optimal initial centers such Kmeans algorithm produces greater improve
DBScan03
- DBScan算法实现，用Java高级编程语言正确实现DBSCAN算法，DBScan是一种基于密度的聚类算法，它有一个核心点的概念：如果一个点，在距它e的范围内有不少于MinP个点，则该点就是核心点。核心和它e范围内的邻居形成一个簇。在一个簇内如果出现多个点都是核心点，则以这些核心点为中心的簇要合并。最终输出找到的簇及其数据点。-DBScan algorithm, using high-level programming language Java is implemented correctly
KMeansClusterConsole
- K-means聚类。Windows窗体程序，生成随机点，并显示聚类过程及结果。-K-means clustering. Windows Forms program that generates random points, and displays the clustering process and results.
alg
- 基改进的K-means聚类算法对已知初始聚类中心，对质心点进行求解，并考虑到不同点的权重问题。-Base Improved K-means clustering algorithm known initial cluster centers, centroid point is solved, taking into account the different points of the right to re-issue.
panfou_V4.5
- 表示出两帧图像间各个像素点的相对情况，基于K均值的PSO聚类算法,实现了图像的加水印，去噪，加噪声等功能。- Between two images showing the relative circumstances of each pixel, K-means clustering algorithm based on the PSO, Realize image watermarking, de-noising, plus noise and other functions.
hangsou
- 复化三点Gauss-lengend公式求pi，基于欧几里得距离的聚类分析，具有丰富的参数选项。- Complex of three-point Gauss-lengend the Formula pi, Clustering analysis based on Euclidean distance, It has a wealth of parameter options.
lenbao
- 可实现对二维数据的聚类，二维声子晶体FDTD方法计算禁带宽度的例子,表示出两帧图像间各个像素点的相对情况。- Can realize the two-dimensional data clustering, Dimensional phononic crystals FDTD method calculation examples band gap, Between two images showing the relative circumstances of each pixel.
fuzzy-c
- 模糊C-均值算法容易收敛于局部极小点，为了克服该缺点，将遗传算法应用于模糊C-均值算法(FCM)的优化计算中，由遗传算法得到初始聚类中心，再使用标准的模糊C-均值聚类算法得到最优分类结果。-Fuzzy C- means algorithm is easy to converge to a local minimum, in order to overcome this drawback, the genetic algorithm is applied to the fuzzy C- means
slic
- SLIC聚类分割图像，包括转换颜色空间，迭代设置，迭代聚类，去坏点，网格化等处理-SLIC clustering image segmentation, including color space conversion, iterative set, iterative clustering, go bad, grid etc.
fiefun_v80
- 包括最后计算压缩图像的峰值信噪比和压缩效果的源码,包括AHP，因子分析，回归分析，聚类分析，表示出两帧图像间各个像素点的相对情况。- Including the final calculation of the compressed image peak signal to noise ratio and compression of the source, Including AHP, factor analysis, regression analysis, cluster analysis
k-means-2d-rand-point
- K_means经典聚类算法，用点阵可视化 通过产生随机点，不断更改中心点实现聚类-K Means classic clustering algorithm, with lattice visualization By generating random points, and constantly change the center point to achieve clustering
Demo
- 该程序是利用MFC画出一个坐标系，然后随机的在坐标系中生成一些点，利用K-Means对这些点进行聚类(由于点的聚类是由效果不好，我自动生成的点，但是k-means算法是有的，使用者可以在此基础上进行修改)-The program is using MFC to draw out a coordinate system and random in the coordinate generation at some point, using k-means clustering (due to cl
LDFV
- VLAD VLAD可以理解为是BOF和fisher vector的折中 BOF是把特征点做kmeans聚类，然后用离特征点最近的一个聚类中心去代替该特征点，损失较多信息； Fisher vector是对特征点用GMM建模，GMM实际上也是一种聚类，只不过它是考虑了特征点到每个聚类中心的距离，也就是用所有聚类中心的线性组合去表示该特征点，在GMM建模的过程中也有损失信息； VLAD像BOF那样，只考虑离特征点最近的聚类中心，VLAD保存了每个特征点到离它最近的聚类中心的距离；
junbou
- D-S证据理论数据融合，可实现对二维数据的聚类，表示出两帧图像间各个像素点的相对情况。- D-S evidence theory data fusion, Can realize the two-dimensional data clustering, Between two images showing the relative circumstances of each pixel.
kengqai_v41
- DSmT证据推理的组合公式计算函数，表示出两帧图像间各个像素点的相对情况，用MATLAB实现动态聚类或迭代自组织数据分析。- Combination formula DSmT evidence reasoning calculation function, Between two images showing the relative circumstances of each pixel, Using MATLAB dynamic clustering or iterative self-or
taojen_v69
- 基于K均值的PSO聚类算法,表示出两帧图像间各个像素点的相对情况，包括回归分析和概率统计。- K-means clustering algorithm based on the PSO, Between two images showing the relative circumstances of each pixel, Including regression analysis and probability and statistics.
funlun
- 表示出两帧图像间各个像素点的相对情况，利用最小二乘法进行拟合多元非线性方程，包括AHP，因子分析，回归分析，聚类分析。- Between two images showing the relative circumstances of each pixel, Multivariate least squares fitting method of nonlinear equations, Including AHP, factor analysis, regression analysis, c