The dynamic clustering algorithm is developed to update the clusters.
最后针对数据库的更新设计了动态聚类算法。
Proposed dynamic clustering algorithm has strong robustness in clustering of time series multi-dimensional data.
本文算法对于时序数据的聚类具有较强的鲁棒性。
A dynamic clustering algorithm was proposed based on consistent matrix of dependent function for time series multi-dimensional data.
根据时序立体数据的特点，提出了基于关联函数一致性矩阵的动态聚类算法。
Objective to introduce a dynamic fuzzy clustering algorithm and use it to do the study of segmentation of the brain in MRI.
目的介绍一种动态模糊聚类算法并利用该算法对磁共振图像进行分割研究。
Whereas, an improved ART2 neural network clustering algorithm is proposed to realize the clustering of dynamic samples, and the simulation results are given out at the same time.
鉴于此，本文又提出了一种改进的ART2网络学习算法来实现动态样本的聚类，同时给出了该方法的实验仿真结果。
Then the time synchronization algorithm based on energy-efficient and hierarchical dynamic clustering is presented.
基于此，本文提出了一种能量有效的多层动态分簇时间同步算法。
At first, ISODATA dynamic clustering is imported to median filtering algorithm. The algorithm can eliminate serious yawp noise and retain image detail.
首先，本文提出一种引入ISODATA动态聚类的医学图像中值滤波算法，此算法既消除了脉冲噪声带来的干扰，又保持了图像的边缘细节。
A clustering-dynamic-growing clustering algorithm was developed based on sentence-words matrix to solve this problem.
为此该文提出了一种基于语句词条矩阵的聚簇式动态增长聚类算法。
This paper describes the relevant concepts and presents a model of CBR based on dynamic data stream mining, and gives an improved clustering algorithm of data stream.
首先阐述了相关概念，接着提出了一种基于动态数据流挖掘的案例推理模型，其中动态数据流挖掘算法采用改进的数据流聚类算法。
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
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