Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information.However,other performance requirements such as life cycle of nodes,stability and security are ...Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information.However,other performance requirements such as life cycle of nodes,stability and security are not set as primary design objectives.This makes data collection ability of vehicular nodes in real application environment inferior.By considering the features of nodes in wireless IoV,such as large scales of deployment,volatility and low time delay,an efficient data collection algorithm is proposed for mobile vehicle network environment.An adaptive sensing model is designed to establish vehicular data collection protocol.The protocol adopts group management in model communication.The vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding nodes.It will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding nodes.In addition,secure data collection between sensing nodes is undertaken as well.The simulation and experiments show that the vehicular node can realize secure and real-time data collection.Moreover,the proposed algorithm is superior in vehicular network life cycle,power consumption and reliability of data collection by comparing to other algorithms.展开更多
This paper describes an improved algorithm for fuzzy c-means clustering of remotely sensed data, by which the degree of fuzziness of the resultant classification is de- creased as comparing with that by a conventional...This paper describes an improved algorithm for fuzzy c-means clustering of remotely sensed data, by which the degree of fuzziness of the resultant classification is de- creased as comparing with that by a conventional algorithm: that is, the classification accura- cy is increased. This is achieved by incorporating covariance matrices at the level of individual classes rather than assuming a global one. Empirical results from a fuzzy classification of an Edinburgh suburban land cover confirmed the improved performance of the new algorithm for fuzzy c-means clustering, in particular when fuzziness is also accommodated in the assumed reference data.展开更多
针对L波段数字航空通信系统(L-band digital aeronautic communication system,LDACS)可用频谱资源有限且易受大功率测距仪(distance measuring equipment,DME)信号干扰的问题,提出一种基于降维循环谱和残差神经网络的频谱感知方法。首...针对L波段数字航空通信系统(L-band digital aeronautic communication system,LDACS)可用频谱资源有限且易受大功率测距仪(distance measuring equipment,DME)信号干扰的问题,提出一种基于降维循环谱和残差神经网络的频谱感知方法。首先理论推导分析了DME信号的循环谱特征;然后利用Fisher判别率(Fisher discriminant rate,FDR)提取循环频率能量最大的向量,通过主成分分析(principal component analysis,PCA)进行预处理特征增强;最后给出数据处理后的循环谱向量与卷积神经网络相结合的实现过程,实现了DME信号的有效检测。仿真结果表明,该方法对噪声不敏感,当信噪比不低于-15 dB时,平均检测概率大于90%。当信噪比不低于-14 dB,检测概率接近100%。展开更多
K-栅栏覆盖是有向传感器网络的研究热点之一.概率感知模型要比0-1模型更贴近实际.而基于概率感知模型的栅栏覆盖还鲜有研究.根据感知概率阈值和感知距离要求,确定节点的虚拟半径.提出一种二元概率栅栏覆盖模型.在这个模型中,相邻2个节...K-栅栏覆盖是有向传感器网络的研究热点之一.概率感知模型要比0-1模型更贴近实际.而基于概率感知模型的栅栏覆盖还鲜有研究.根据感知概率阈值和感知距离要求,确定节点的虚拟半径.提出一种二元概率栅栏覆盖模型.在这个模型中,相邻2个节点的虚拟感知圆两两相切.在此基础上提出了最少节点的概率栅栏构建算法(construction of probabilistic barrier of minimum node,CPBMN).首先根据二元概率栅栏模型确定节点的目标位置,再通过匈牙利算法选用移动距离之和最少的移动节点移动到目标位置形成栅栏覆盖,缺少移动节点的子区域,选择附近区域的剩余移动节点修补形成1-栅栏覆盖.水平相邻的2个子区域之间构建竖直栅栏,这些子区域的概率1-栅栏合起来构成整个区域的概率K-栅栏覆盖.仿真结果证明:该方法能够有效形成概率栅栏,最多比其他栅栏构建算法节省70%能耗.展开更多
基金supported by the National Nature Science Foundation of China(Grant61572188)A Project Supported by Scientif ic Research Fund of Hunan Provincial Education Department(14A047)+4 种基金the Natural Science Foundation of Fujian Province(Grant no.2014J05079)the Young and Middle-Aged Teachers Education Scientific Research Project of Fujian province(Grant nos.JA13248JA14254 and JA15368)the special scientific research funding for colleges and universities from Fujian Provincial Education Department(Grant no.JK2013043)the Research Project supported by Xiamen University of Technology(YKJ15019R)
文摘Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information.However,other performance requirements such as life cycle of nodes,stability and security are not set as primary design objectives.This makes data collection ability of vehicular nodes in real application environment inferior.By considering the features of nodes in wireless IoV,such as large scales of deployment,volatility and low time delay,an efficient data collection algorithm is proposed for mobile vehicle network environment.An adaptive sensing model is designed to establish vehicular data collection protocol.The protocol adopts group management in model communication.The vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding nodes.It will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding nodes.In addition,secure data collection between sensing nodes is undertaken as well.The simulation and experiments show that the vehicular node can realize secure and real-time data collection.Moreover,the proposed algorithm is superior in vehicular network life cycle,power consumption and reliability of data collection by comparing to other algorithms.
文摘This paper describes an improved algorithm for fuzzy c-means clustering of remotely sensed data, by which the degree of fuzziness of the resultant classification is de- creased as comparing with that by a conventional algorithm: that is, the classification accura- cy is increased. This is achieved by incorporating covariance matrices at the level of individual classes rather than assuming a global one. Empirical results from a fuzzy classification of an Edinburgh suburban land cover confirmed the improved performance of the new algorithm for fuzzy c-means clustering, in particular when fuzziness is also accommodated in the assumed reference data.
文摘K-栅栏覆盖是有向传感器网络的研究热点之一.概率感知模型要比0-1模型更贴近实际.而基于概率感知模型的栅栏覆盖还鲜有研究.根据感知概率阈值和感知距离要求,确定节点的虚拟半径.提出一种二元概率栅栏覆盖模型.在这个模型中,相邻2个节点的虚拟感知圆两两相切.在此基础上提出了最少节点的概率栅栏构建算法(construction of probabilistic barrier of minimum node,CPBMN).首先根据二元概率栅栏模型确定节点的目标位置,再通过匈牙利算法选用移动距离之和最少的移动节点移动到目标位置形成栅栏覆盖,缺少移动节点的子区域,选择附近区域的剩余移动节点修补形成1-栅栏覆盖.水平相邻的2个子区域之间构建竖直栅栏,这些子区域的概率1-栅栏合起来构成整个区域的概率K-栅栏覆盖.仿真结果证明:该方法能够有效形成概率栅栏,最多比其他栅栏构建算法节省70%能耗.
