Identifying influential nodes in complex networks is of both theoretical and practical importance. Existing methods identify influential nodes based on their positions in the network and assume that the nodes are homo...Identifying influential nodes in complex networks is of both theoretical and practical importance. Existing methods identify influential nodes based on their positions in the network and assume that the nodes are homogeneous. However, node heterogeneity （i.e., different attributes such as interest, energy, age, and so on ） ubiquitously exists and needs to be taken into consideration. In this paper, we conduct an investigation into node attributes and propose a graph signal pro- cessing based centrality （GSPC） method to identify influential nodes considering both the node attributes and the network topology. We first evaluate our GSPC method using two real-world datasets. The results show that our GSPC method effectively identifies influential nodes, which correspond well with the underlying ground truth. This is compatible to the previous eigenvector centrality and principal component centrality methods under circumstances where the nodes are homogeneous. In addition, spreading analysis shows that the GSPC method has a positive effect on the spreading dynamics.展开更多
The key methods of detection and classification of the electroencephalogram(EEG) used in recent years are introduced . Taking EEG for example, the design plan of Kohonen neural network system based on detection and cl...The key methods of detection and classification of the electroencephalogram(EEG) used in recent years are introduced . Taking EEG for example, the design plan of Kohonen neural network system based on detection and classification of complex signals is proposed, and both the network design and signal processing are analyzed, including pre-processing of signals, extraction of signal features, classification of signal and network topology, etc.展开更多
To design approximately linear-phase complex coefficient finite impulse response （FIR） digital filters with arbitrary magnitude and group delay responses, a novel neural network approach is studied. The approach is ...To design approximately linear-phase complex coefficient finite impulse response （FIR） digital filters with arbitrary magnitude and group delay responses, a novel neural network approach is studied. The approach is based on a batch back-propagation neural network algorithm by directly minimizing the real magnitude error and phase error from the linear-phase to obtain the filter＇s coefficients. The approach can deal with both the real and complex coefficient FIR digital filters design problems. The main advantage of the proposed design method is the significant reduction in the group delay error. The effectiveness of the proposed method is illustrated with two optimal design examples.展开更多
基于对语音、视频处理实时性和稳定性的高要求,以可编程数字信号处理器(Digital Signal Processor,DSP)为主体进行研究,通过分析DSP处理器的系统总体,介绍系统中不同环节的作用,设计出可以有效提高数据传输实时性和稳定性的数字信号处...基于对语音、视频处理实时性和稳定性的高要求,以可编程数字信号处理器(Digital Signal Processor,DSP)为主体进行研究,通过分析DSP处理器的系统总体,介绍系统中不同环节的作用,设计出可以有效提高数据传输实时性和稳定性的数字信号处理系统,以提高语音和视频处理效率,助力企业实现可持续发展。展开更多
人群在城市内部空间中的流动是社会活力和资源分配的直接体现,是城市交通规划管理的重要依据。融合手机信令大数据和POI(point of interests)数据,对福州市主城区内的交通小区进行功能分区并构建了交通小区之间的空间交互网络,采用复杂...人群在城市内部空间中的流动是社会活力和资源分配的直接体现,是城市交通规划管理的重要依据。融合手机信令大数据和POI(point of interests)数据,对福州市主城区内的交通小区进行功能分区并构建了交通小区之间的空间交互网络,采用复杂网络方法对各类型功能区的中心性地位及出行距离衰减效应进行了分析。结果表明:福州市主城区功能区以居住及公共服务相关功能区为主。鼓楼区和台江区的人流量最为活跃,仓山区及晋安区的内部空间交互格局存在显著的不平衡现象。各功能区的中心性地位存在明显的空间和周期差异,科教文化及商服类型功能区的中心性普遍较高。居住用地与其他功能区之间的距离衰减效应受到时段的影响较大。基于以上结果可对城市公共交通优化提供一定支持。展开更多
基金supported by the National Natural Science Foundation of China(Grant No.61231010)the Fundamental Research Funds for the Central Universities,China(Grant No.HUST No.2012QN076)
文摘Identifying influential nodes in complex networks is of both theoretical and practical importance. Existing methods identify influential nodes based on their positions in the network and assume that the nodes are homogeneous. However, node heterogeneity （i.e., different attributes such as interest, energy, age, and so on ） ubiquitously exists and needs to be taken into consideration. In this paper, we conduct an investigation into node attributes and propose a graph signal pro- cessing based centrality （GSPC） method to identify influential nodes considering both the node attributes and the network topology. We first evaluate our GSPC method using two real-world datasets. The results show that our GSPC method effectively identifies influential nodes, which correspond well with the underlying ground truth. This is compatible to the previous eigenvector centrality and principal component centrality methods under circumstances where the nodes are homogeneous. In addition, spreading analysis shows that the GSPC method has a positive effect on the spreading dynamics.
文摘The key methods of detection and classification of the electroencephalogram(EEG) used in recent years are introduced . Taking EEG for example, the design plan of Kohonen neural network system based on detection and classification of complex signals is proposed, and both the network design and signal processing are analyzed, including pre-processing of signals, extraction of signal features, classification of signal and network topology, etc.
基金supported by the National Natural Science Foundation of China(6087602250677014)+2 种基金the High-Tech Research and Development Program of China(2006AA04A104)the Hunan Provincial Natural Science Foundation of China (06JJ202407JJ5076).
文摘To design approximately linear-phase complex coefficient finite impulse response （FIR） digital filters with arbitrary magnitude and group delay responses, a novel neural network approach is studied. The approach is based on a batch back-propagation neural network algorithm by directly minimizing the real magnitude error and phase error from the linear-phase to obtain the filter＇s coefficients. The approach can deal with both the real and complex coefficient FIR digital filters design problems. The main advantage of the proposed design method is the significant reduction in the group delay error. The effectiveness of the proposed method is illustrated with two optimal design examples.
文摘基于对语音、视频处理实时性和稳定性的高要求,以可编程数字信号处理器(Digital Signal Processor,DSP)为主体进行研究,通过分析DSP处理器的系统总体,介绍系统中不同环节的作用,设计出可以有效提高数据传输实时性和稳定性的数字信号处理系统,以提高语音和视频处理效率,助力企业实现可持续发展。
文摘人群在城市内部空间中的流动是社会活力和资源分配的直接体现,是城市交通规划管理的重要依据。融合手机信令大数据和POI(point of interests)数据,对福州市主城区内的交通小区进行功能分区并构建了交通小区之间的空间交互网络,采用复杂网络方法对各类型功能区的中心性地位及出行距离衰减效应进行了分析。结果表明:福州市主城区功能区以居住及公共服务相关功能区为主。鼓楼区和台江区的人流量最为活跃,仓山区及晋安区的内部空间交互格局存在显著的不平衡现象。各功能区的中心性地位存在明显的空间和周期差异,科教文化及商服类型功能区的中心性普遍较高。居住用地与其他功能区之间的距离衰减效应受到时段的影响较大。基于以上结果可对城市公共交通优化提供一定支持。
