论文标题
大脑网络之间具有流行网络测量算法的统计比较
Statistical Comparison among Brain Networks with Popular Network Measurement Algorithms
论文作者
论文摘要
在这项研究中，已经将许多流行的网络测量算法应用于几个大脑网络（基于算法的适用性），以在这些流行的网络测量中找到统计相关性，这将帮助科学家了解这些流行的网络测量算法及其对大脑网络的适用性。通过分析这些网络测量算法之间相关性的结果，还总结了所选脑网络之间的统计比较。除此之外，要了解每个大脑网络，每个大脑网络和每个大脑网络分布直方图的可视化已被推断。已经选择了六种网络测量算法，以根据这些网络测量算法的适用性将时间应用于16个大脑网络上，并将这些网络测量结果的结果放入相关方法中，以显示每个大脑网络的这六个网络测量算法之间的关系。最后，相关性的结果总结了，以显示这16个大脑网络之间的统计比较。
In this research, a number of popular network measurement algorithms have been applied to several brain networks (based on applicability of algorithms) for finding out statistical correlation among these popular network measurements which will help scientists to understand these popular network measurement algorithms and their applicability to brain networks. By analysing the results of correlations among these network measurement algorithms, statistical comparison among selected brain networks has also been summarized. Besides that, to understand each brain network, the visualization of each brain network and each brain network degree distribution histogram have been extrapolated. Six network measurement algorithms have been chosen to apply time to time on sixteen brain networks based on applicability of these network measurement algorithms and the results of these network measurements are put into a correlation method to show the relationship among these six network measurement algorithms for each brain network. At the end, the results of the correlations have been summarized to show the statistical comparison among these sixteen brain networks.
