Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the ...Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the scoring functions under high dimensional cases.We study the construction of confidence regions for the parameters in spatial autoregressive models with spatial autoregressive disturbances(SARAR models)with high dimension of parameters by using the NBEL method.It is shown that the NBEL ratio statistics are asymptoticallyχ^(2)-type distributed,which are used to obtain the NBEL based confidence regions for the parameters in SARAR models.A simulation study is conducted to compare the performances of the NBEL and the usual EL methods.展开更多
多重信号分类(multiple signal classification,MUSIC)算法采用全向天线作为阵列阵元,为提升算法的抗干扰能力和定位精度,针对变电站局部放电检测采用定向天线阵列进行定位的具体应用,将天线方向图增益作为阵列流形系数,提出并推导了用...多重信号分类(multiple signal classification,MUSIC)算法采用全向天线作为阵列阵元,为提升算法的抗干扰能力和定位精度,针对变电站局部放电检测采用定向天线阵列进行定位的具体应用,将天线方向图增益作为阵列流形系数,提出并推导了用于定向天线阵列定位的MUSIC算法,在运用克拉美罗界和二阶统计信噪比估计理论分析算法定位误差基础上,通过搭建仿真模型进一步验证算法的性能。仿真结果表明,对于常规选定频带的局部放电信号,基于定向天线的MUSIC算法可在天线方向图增益大于1的来波方向范围内提升定位精度,且定位精度与天线增益大小成正相关。采用所设计的方向图增益达6 dB的定向天线阵列,在信噪比为0 dB的条件下信源定位误差为0.806°,而经典MUSIC算法的定位误差达到17.403°。展开更多
Cloud computing has emerged as a leading computing paradigm,with an increasing number of geographic information(geo-information) processing tasks now running on clouds.For this reason,geographic information system/rem...Cloud computing has emerged as a leading computing paradigm,with an increasing number of geographic information(geo-information) processing tasks now running on clouds.For this reason,geographic information system/remote sensing(GIS/RS) researchers rent more public clouds or establish more private clouds.However,a large proportion of these clouds are found to be underutilized,since users do not deal with big data every day.The low usage of cloud resources violates the original intention of cloud computing,which is to save resources by improving usage.In this work,a low-cost cloud computing solution was proposed for geo-information processing,especially for temporary processing tasks.The proposed solution adopted a hosted architecture and can be realized based on ordinary computers in a common GIS/RS laboratory.The usefulness and effectiveness of the proposed solution was demonstrated by using big data simplification as a case study.Compared to commercial public clouds and dedicated private clouds,the proposed solution is more low-cost and resource-saving,and is more suitable for GIS/RS applications.展开更多
The problem of designing a digital frontend (DFE) was considered which can dynamically access or sense dual bands in any radio frequency (RF) regions without requiring hardware changes. In particular, second-order ban...The problem of designing a digital frontend (DFE) was considered which can dynamically access or sense dual bands in any radio frequency (RF) regions without requiring hardware changes. In particular, second-order bandpass sampling (BPS) as a technique that enables to realize the multiband reception function was discussed. In a second-order BPS system, digital reconstruction filters were utilized to eliminate the interferences generated while down converting arbitrarily positioned RF-band signals by using the direct digitization method. However, the inaccuracy in the phase shift or the amplitude mismatch between the two sample streams may cause insufficient rejection of interference. Practical problems were studied, such as performance degradation in signal-to-interference ratio (SIR) and compensation methods to overcome them. In order to demonstrate the second- order BPS as a flexible DFE suitable for software-defined radio (SDR) or cognitive radio (CR), a DFE testbed with a reconfigurable structure was implemented. Moreover, with a view to further demonstrate the proposed compensation algorithms, experimental results show that dual bands are received simultaneously.展开更多
基金Supported by the National Natural Science Foundation of China(12061017,12361055)the Research Fund of Guangxi Key Lab of Multi-source Information Mining&Security(22-A-01-01)。
文摘Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the scoring functions under high dimensional cases.We study the construction of confidence regions for the parameters in spatial autoregressive models with spatial autoregressive disturbances(SARAR models)with high dimension of parameters by using the NBEL method.It is shown that the NBEL ratio statistics are asymptoticallyχ^(2)-type distributed,which are used to obtain the NBEL based confidence regions for the parameters in SARAR models.A simulation study is conducted to compare the performances of the NBEL and the usual EL methods.
文摘多重信号分类(multiple signal classification,MUSIC)算法采用全向天线作为阵列阵元,为提升算法的抗干扰能力和定位精度,针对变电站局部放电检测采用定向天线阵列进行定位的具体应用,将天线方向图增益作为阵列流形系数,提出并推导了用于定向天线阵列定位的MUSIC算法,在运用克拉美罗界和二阶统计信噪比估计理论分析算法定位误差基础上,通过搭建仿真模型进一步验证算法的性能。仿真结果表明,对于常规选定频带的局部放电信号,基于定向天线的MUSIC算法可在天线方向图增益大于1的来波方向范围内提升定位精度,且定位精度与天线增益大小成正相关。采用所设计的方向图增益达6 dB的定向天线阵列,在信噪比为0 dB的条件下信源定位误差为0.806°,而经典MUSIC算法的定位误差达到17.403°。
基金Project(41401434)supported by the National Natural Science Foundation of China
文摘Cloud computing has emerged as a leading computing paradigm,with an increasing number of geographic information(geo-information) processing tasks now running on clouds.For this reason,geographic information system/remote sensing(GIS/RS) researchers rent more public clouds or establish more private clouds.However,a large proportion of these clouds are found to be underutilized,since users do not deal with big data every day.The low usage of cloud resources violates the original intention of cloud computing,which is to save resources by improving usage.In this work,a low-cost cloud computing solution was proposed for geo-information processing,especially for temporary processing tasks.The proposed solution adopted a hosted architecture and can be realized based on ordinary computers in a common GIS/RS laboratory.The usefulness and effectiveness of the proposed solution was demonstrated by using big data simplification as a case study.Compared to commercial public clouds and dedicated private clouds,the proposed solution is more low-cost and resource-saving,and is more suitable for GIS/RS applications.
基金Research financially supported by Changwon National University in 2009-2010the Second Stage of Brain Korea 21 Projects
文摘The problem of designing a digital frontend (DFE) was considered which can dynamically access or sense dual bands in any radio frequency (RF) regions without requiring hardware changes. In particular, second-order bandpass sampling (BPS) as a technique that enables to realize the multiband reception function was discussed. In a second-order BPS system, digital reconstruction filters were utilized to eliminate the interferences generated while down converting arbitrarily positioned RF-band signals by using the direct digitization method. However, the inaccuracy in the phase shift or the amplitude mismatch between the two sample streams may cause insufficient rejection of interference. Practical problems were studied, such as performance degradation in signal-to-interference ratio (SIR) and compensation methods to overcome them. In order to demonstrate the second- order BPS as a flexible DFE suitable for software-defined radio (SDR) or cognitive radio (CR), a DFE testbed with a reconfigurable structure was implemented. Moreover, with a view to further demonstrate the proposed compensation algorithms, experimental results show that dual bands are received simultaneously.
