cluster in quest聚类算法是基于密度和网格的聚类算法。对于大型数据库的高维数据聚类集合。-cluster in quest clustering algorithm is based on the density of the grid and clustering algorithm. For large database of high-dimensional data clustering pool.

Optics聚类算法 OPTICS没有显示地产生一个数据集合簇，它为自动和交互地聚类分析计算一个簇次序。这个次序代表了数据基于密度地聚类结构。它包含地信息，等同于从一个宽广地参数设置范围所获得的基于密度的聚类-Optics do not show clustering algorithm OPTICS to produce a collection of data clusters, it is automatically and interactively computing cluster

这是一种改进的基于密度的聚类算法，其侧重点在于，点与线的分离-This is an improved clustering algorithm based on density, its focus is on the separation point and the line

计算目标和海洋回波的功率谱密度,BP神经网络的整个训练过程,基于K均值的PSO聚类算法。- Calculating a target and ocean echo power spectral density, The entire training process BP neural network, K-means clustering algorithm based on the PSO.

计算目标和海洋回波的功率谱密度,用MATLAB实现动态聚类或迭代自组织数据分析，基于小波变换的数字水印算法matlab代码。- Calculating a target and ocean echo power spectral density, Using MATLAB dynamic clustering or iterative self-organizing data analysis, Based on wavelet transform digital watermarking al