Massive MIMO system with FDD mode can support very high spatial reuse, however, the improvement of system performance is greatly limited due to the similarity between users and the overhead of uplink CSI feedback. In ...
详细信息
ISBN:
(纸本)9781728118468
Massive MIMO system with FDD mode can support very high spatial reuse, however, the improvement of system performance is greatly limited due to the similarity between users and the overhead of uplink CSI feedback. In this paper, a clustering algorithm based on users multi-dimensional features for Massive MIMO System is proposed to mitigate inter-user interference. Specifically, it includes searching and eliminating users with noise spots, analyzing and defining user space-related and non-space-related features, and reducing the dimension of three-dimensional features. Then, inspired by the Affinity propagation (AP) clustering algorithm, we propose the scheme considering the similarity between users for clustering. The simulation results show that the proposed scheme can significantly reduce the inter-user interference while improving the average SINR of users.
' In this paper, we present certain algorithms for clustering the vertices of fuzzy graphs(FGs) and intuitionistic fuzzy graphs(IFGs). These algorithms are based on the edge density of the given graph. We apply th...
详细信息
' In this paper, we present certain algorithms for clustering the vertices of fuzzy graphs(FGs) and intuitionistic fuzzy graphs(IFGs). These algorithms are based on the edge density of the given graph. We apply the algorithms to practical problems to derive the most prominent cluster among them. We also introduce parameters for intuitionistic fuzzy graphs.
We adopt clustering algorithm to improve segmentation accuracy. In this paper, 3D laser scanning platform was built to obtain the spatial 3D point cloud data. And then we extracted the point cloud data for two planar ...
详细信息
ISBN:
(纸本)9781538660058
We adopt clustering algorithm to improve segmentation accuracy. In this paper, 3D laser scanning platform was built to obtain the spatial 3D point cloud data. And then we extracted the point cloud data for two planar features. K-means algorithm, density-based clustering algorithm and density peak clustering algorithm were employed to split the 3D point cloud of the two planes. After clustering, we compared and analyzed the clustering results of the three clustering algorithms. More importantly, we also found that for peak density clustering, the threshold value is related to its sensitivity to noise points. After fitting the two planes, the verticality of two planes was also calculated. We analyzed the results and summarized the criterion for selecting thresholds.
An important feature of structural data especially those from structural determination and protein-ligand docking programs is that their distribution could be both uniform and non-uniform. Traditional clustering algor...
详细信息
ISBN:
(纸本)9783319052694;9783319052687
An important feature of structural data especially those from structural determination and protein-ligand docking programs is that their distribution could be both uniform and non-uniform. Traditional clustering algorithms developed specifically for non-uniformly distributed data may not be adequate for their classification. Here we present a geometric partitional algorithm that could be applied to both uniformly and non-uniformly distributed data. The algorithm is a top-down approach that recursively selects the outliers as the seeds to form new clusters until all the structures within a cluster satisfy certain requirements. The applications of the algorithm to a diverse set of data from NMR structure determination, protein-ligand docking and simulation show that it is superior to the previous clustering algorithms for the identification of the correct but minor clusters. The algorithm should be useful for the identification of correct docking poses and for speeding up an iterative process widely used in NMR structure determination.
The joint combat of multiple fighter formations is an important means of attack in modern warfare. We can respond in a timely manner if the enemy's flight formations can be predicted in advance. That is significan...
详细信息
ISBN:
(纸本)9781728185750
The joint combat of multiple fighter formations is an important means of attack in modern warfare. We can respond in a timely manner if the enemy's flight formations can be predicted in advance. That is significant to our combat deployment and countermeasures. Based on the needs and characteristics of aircraft formation analysis and prediction, this paper uses a density-based clustering algorithm to automatically identify flight formations, and uses a large amount of real aircraft data for testing. The test results of the examples show that the proposed method can be more accurate to identify aircraft flying in formation.
This paper describes navigation method usable in agriculture plant row for mobile robot. The proposed method with clustering algorithm uses data obtained by Hokuyo laser sensor. Using the created solution it is possib...
详细信息
ISBN:
(纸本)9781728103624
This paper describes navigation method usable in agriculture plant row for mobile robot. The proposed method with clustering algorithm uses data obtained by Hokuyo laser sensor. Using the created solution it is possible to determine plant in a row when mobile robot using the local navigation principle. Crops in a row are characteristic waypoints that create the vertices of the polygon. From this polygon the center of gravity is calculated, which determines the center position of the plant row. From this polygon the center of gravity is calculated, which determines the center position of the plant row. This position is used for mobile robot control algorithm. The processed data by scanners provide information not only on waypoints but also on any obstacles in the agricultural plant row.
The efficient subdivision of a sensor network into uniform clusters of physically close nodes is an important building block in the design of efficient upper layer network functions such as routing, broadcast, data ag...
详细信息
ISBN:
(纸本)9781424419814
The efficient subdivision of a sensor network into uniform clusters of physically close nodes is an important building block in the design of efficient upper layer network functions such as routing, broadcast, data aggregation, and query processing. This paper analyzes a low energy adaptive clustering hierarchy (LEACH) in terms of the optimum number of clusters and demonstrates through simulation that the optimum number calculated are not suitable for sensor networks including large number of nodes or covering large area. Based on the analysis results, we give a new formula of calculating the optimum number of clusters on an improved data gathering model. To decrease the energy dissipation further, we develop a new efficient uniform clustering algorithm in ad-hoc sensor networks. Simulation results show that it achieves fairly uniform cluster-head distribution across the network.
Energy efficient clustering protocols are deeply studied for low power, multi-functional wireless sensors networks (WSNs), clustering have to ensure connectivity and reliability in WSN even in large scale environment....
详细信息
ISBN:
(纸本)9781538653050
Energy efficient clustering protocols are deeply studied for low power, multi-functional wireless sensors networks (WSNs), clustering have to ensure connectivity and reliability in WSN even in large scale environment. In this paper, we present a new clustering approach called the Fixed Competition-based clustering Approach (FCBA) based routing algorithm to fairly use the energy of the sensors to maximize the network lifetime. The Selecting of cluster heads with FCBA is performed based upon a residual energy and the distances among the cluster heads. The simulation results are given to validate the analytical results. The experimental results indicate that proposed protocol leads to reduction of sensor's nodes energy consumption and prolongs the network lifetime, significantly.
In order to accurately extract landslide disaster information from SAR images, we propose a clustering algorithm for landslide detection using multi-temporal fully polarimetric SAR image. By combining Freeman-Durden d...
详细信息
ISBN:
(纸本)9781538691540
In order to accurately extract landslide disaster information from SAR images, we propose a clustering algorithm for landslide detection using multi-temporal fully polarimetric SAR image. By combining Freeman-Durden decomposition with H /alpha /A decomposition method, this algorithm makes full use of scattering power and scattering entropy information. Furthermore, a hierarchical method is proposed to overcome the drawback that fuzzy membership function family of multi-region classification cannot always satisfy the constraint conditions to guarantee functional convexity. Such method ensures that the constraint conditions can always be satisfied and improves the accuracy of classification. Finally, the landslide disaster area is accurately extracted from the two classification maps by change detection. The results of the C-band RadarSat-2 data are provided to demonstrate its competitive general performance of image classification.
This paper proposed an efficient PSO clustering algorithm with point symmetry distance based on cooperative evolution strategy. It not only determined the number of clusters, but also detected the proper partitions in...
详细信息
ISBN:
(纸本)9781845648299;9781845648282
This paper proposed an efficient PSO clustering algorithm with point symmetry distance based on cooperative evolution strategy. It not only determined the number of clusters, but also detected the proper partitions in data sets when the data sets possess the property of symmetry. In the algorithm, a new point symmetry distance is used to compute the similarity instead of the Euclid distance. Cooperative evolution strategy with multi-populations is introduced to prevent the PSO algorithm from trapping into the local optimal solution. The performance of the proposed algorithm is tested in two artificial data sets. The simulation results show that the performance of the algorithm is better than other algorithms mentioned in this paper.
暂无评论