二维声子晶体FDTD方法计算禁带宽度的例子,用MATLAB实现动态聚类或迭代自组织数据分析，表示出两帧图像间各个像素点的相对情况。- Dimensional phononic crystals FDTD method calculation examples band gap, Using MATLAB dynamic clustering or iterative self-organizing data analysis, Between two images showing the rel

模拟八线激光雷达产生点云数据，实现目标聚类，并对聚类的目标进行跟踪。(Simulated eight line lidar generates point cloud data, achieves target clustering, and tracks the clustering targets.)

K-means聚类算法，基于PSO改的聚类算法，对初始点的选择进行优化(K-means clustering algorithm, based on PSO modified clustering algorithm, optimized the selection of the initial point.)

介绍了k-means 均值聚类，能很好的将离散的点，聚类成几个指定的聚合点。(The K-means mean clustering is introduced, and the discrete points can be well clustered into several designated aggregation points.)

有代表性的基于密度的聚类算法 ，将簇定义为密度相连的点的最大集合，能够把具有足够高密度的区域划分为簇，并可在噪声的空间数据库中发现任意形状的聚类。(DBSCAN(Density-Based Spatial Clustering of Applications with Noise))