搜索结果: 1-13 共查到“信息与通信工程 K-means”相关记录13条 . 查询时间(0.307 秒)
GF-3 SAR IMAGE DESPECKLING BASED ON THE IMPROVED NON-LOCAL MEANS USING NON-SUBSAMPLED SHEARLET TRANSFORM
GF-3 SAR non-subsampled Shearlet transform image despeckling improved Non-Local Means
2018/5/15
GF-3 synthetic aperture radar (SAR) images are rich in information and have obvious sparse features. However, the speckle appears in the GF-3 SAR images due to the coherent imaging system and it hinde...
MONITORING OF HORIZONTAL MOVEMENTS OF HIGH-RISE BUILDINGS AND TOWER TRANSMITTERS BY MEANS OF GROUND-BASED INTERFEROMETRIC RADAR
Ground-based radar interferometry Horizontal movements Deformations High-rise buildings Tower transmitters
2018/5/8
The paper describes possibilities of the relatively new technics – ground based radar interferometry for precise determining of deformation of structures. Special focus on the horizontal movements of ...
一种K-means改进算法的软扩频信号伪码序列盲估计
软扩频信号 伪码序列 K-means聚类 盲估计
2018/5/21
针对软扩频信号因采用了编码技术使得伪码序列难以估计的问题，该文提出一种基于K-means聚类改进的软扩频信号伪码序列盲估计方法。该方法首先以单倍伪码周期的窗长对接收信号进行数据分段以构造观测数据矩阵，其次利用相似测度的理论从观测数据中寻找出K-means算法最优的初始聚类中心点，然后通过搜索平均轮廓系数(Silhouette Coefficient, SC)最大的绝对值以完成伪码集合规模数的估计，...
针对传统隐私保护方法无法应对任意背景知识下恶意分析的问题，提出了分布式环境下满足差分隐私的k-means算法。该算法利用MapReduce计算框架，由主任务控制k-means迭代执行；指派Mapper分任务独立并行计算各数据片中每条记录与聚类中心的距离并标记其属于的聚类；指派Reducer分任务计算同一聚类中的记录数量num和属性向量之和sum，并利用Laplace机制产生的噪声扰动num和sum...
LIDAR Data Classification Using Hierarchical K-Means Clustering
Remote Sensing LIDAR Hierarchical Classification DTM Multiresolution
2015/12/8
This paper deals with lidar point cloud filtering and classification for modelling the Terrain and more generally for scene segmentation. In this study, we propose to use the well-known K-means cluste...
The Roman City of Uxama Argeala (Soria,Spain) and its Study by Means of Remote Sensing and Digital Cartography
Remote Sensing Image Processing Digital Cartography Roman Town Urbanism
2015/11/12
During the last ten years, we have undertaken a research in order to elaborate a working methodology to study archaeological sites without excavating, by means of using no destructive interventions as...
SEMI-AUTOMATED CLASSIFICATION OF URBAN AREAS BY MEANS OF HIGH RESOLUTION RADAR DATA
High Resolution SAR Urban Areas Detection Contextual Analysis Texture Automation
2015/7/29
Almost two thirds of the world’s population will live in cities by 2030. Thus, human settlements typify the most dynamic regions on
earth. To cope with this development urban planning and management...
面向MANET异常检测的分布式遗传k-means研究
移动自组网 异常入侵检测 k-means聚类 Map Reduce 遗传算法 划分贡献度
2015/12/21
针对移动自组网(MANET,mobile ad hoc networks)入侵检测过程中的攻击类型多样性和监测数据海量性问题,提出了一种基于改进k-means算法的MANET异常检测方法。通过引入划分贡献度的概念,可合理地计算各维特征在检测中占有的权重,并将遗传算法与快速聚类检测算法k-means相结合,解决了聚类检测结果容易陷入局部最优的问题,进而,提出了以上检测算法在Map Reduce框架下...
针对分布式BPEL引擎在云中的放置问题开展研究，提出了一种基于K-means的分布式BPEL引擎放置机制，该机制将BPEL引擎放置问题模型化为相关最优化数学模型，并且将该模型映射到K-means算法进行求解。该机制还讨论了算法在不同网络拓扑随机图、树形网络拓扑的应用。最后利用统计软件R进行了相关实验仿真，仿真结果显示该放置机制可优化服务调用所占用的带宽资源。
基于最小聚类求解k-means问题算法
样本子集 k-means问题 随机近似算法
2012/4/19
针对每个划分子集要求至少满足一定数量点的k-means问题，设计了该问题的随机近似算法。1)给出一个样本子集，证明了该样本子集至少以1/2的概率包含每个最优子集中至少一个点，进一步设计近似度为2的随机算法。2) 设计了该问题的(1+e)随机近似算法，算法的成功概率至少为3/2k+2。3) 利用取样技术，设计了k-means问题的局部搜索随机算法。
一种用于文本聚类的改进k-means算法
文本聚类 k-means 向量空间模型 局部迭代
2009/11/20
k-means是目前常用的文本聚类算法,针对其最终搜索的局部极值与全局最优解偏差较大的缺点,采用一种基于局部搜索优化的思想来改进算法,并推导出目标函数的变化公式。根据目标函数值的改变对聚类结果作再次划分后,继续k-means迭代,拓展其搜索范围。理论分析和实验结果表明修改后的算法能有效地提高聚类的质量,且计算复杂度仍与数据集文本总数呈线性变化。
Interpretation of Radar Signatures Observed in SAR Images of Ice Island T-3 by Means of Backscatter Modelling
Radar Signatures Observed in SAR Images Ice Island T-3 Backscatter Modelling
2014/4/15
Interpretation of Radar Signatures Observed in SAR Images of Ice Island T-3 by Means of Backscatter Modelling.
Rainfall Estimation by Means of a Meteorological Radar: an Innovative Approach Using Neutral Networks
Rainfall Estimation Means of a Meteorological Radar an Innovative Approach Neutral Networks
2014/4/15
Rainfall Estimation by Means of a Meteorological Radar: an Innovative Approach Using Neutral Networks。