A Direct Derivation of the Exact Fisher Information Matrix for Bivariate Bessel Distribution of Type I

This paper deals with a direct derivation of Fisher’s information matrix for bivariate Bessel distribution of type I. Some tools for the numerical computation and some tabulations of the Fisher’s information matrix are provided.

Research on Industrial Relevance Degree and Industrial Financial Situation Risk Matrix Construction——Based on Chinese Information Technology Industry

Based on Input-Output Table in 2010 issued by National Bureau of Statistics of China, with the help of input-output model and with the calculation of indexes of industrial relevance degree in Chinese information technology industry, the paper reveals the industrial relevance in Chinese information technology industry. The paper also selects the relevant industries which are highly associated with the development of Chinese information technology industry based on industrial relevance degree to analyze the influences of these industries on the financial situation risk fluctuation in information technology industry and to design the matrix of financial situation risk in information technology industry. Then, the paper offers countermeasures and suggestions for the development of our information technology industry.

The matrix representation for the mathematic structure of Shannon’s information measures

Shannon’s information measure is a crucial concept in Information Theory. And the research, for the mathematics structure of Shannon’s information measure, is to recognize the essence of information measure. The linear relation between Shannon’s information measures and some signed measure space by using the formal symbols substitution rule is discussed. Furthermore, the coefficient matrix recurrent formula of the linear relation is obtained. Then the coefficient matrix is proved to be invertible via mathematical induction. This shows that the linear relation is one-to-one, and according to this, it can be concluded that a compact space can be generated from Shannon’s information measures.

Research on fault-tolerant control of networked control systems based on information scheduling

A kind of networked control system is studied; the networked control system with noise disturbance is modeled based on information scheduling and control co-design. Augmented state matrix analysis method is introduced, and robust fault-tolerant control problem of networked control systems with noise disturbance under actuator failures is studied. The parametric expression of the controller under actuator failures is given. Furthermore, the result is analyzed by simulation tests, which not only satisfies the networked control systems stability, but also decreases the data information number in network channel and makes full use of the network resources.

Evaluation Criteria Based on Mutual Information for Classifications Including Rejected Class

与用表演措施的常规评估标准不同，信息理论基于在场的标准在机器学习的应用的一个唯一的有益的特征。然而，我们仍然远非正在拥有熵类型标准的深入的理解，说，在与常规基于表演的标准的关系。这份报纸学习通用分类问题，它包括一拒绝，或未知，班。我们在场基本公式和分类基于信息学习的图解的图理论。一个靠近形式的方程为通用分类问题在规范的相互的信息和扩充混乱矩阵之间被导出。敏感方程的三个定理和定理集合为学习在相互的信息和常规表演索引之间的关系被给。我们也与常规标准比较举与相互的信息标准的优点和限制有关的数字例子和几讨论。

OPERATOR-VALUED FREE FISHER INFORMATION OF RANDOM MATRICES

The free Fisher information of an operator random matrix is studied. When the covariance of a random matrix is a conditional expectation, the free Fisher information of such a matrix is the double of this conditional expectation’s Watatani index.

Novel Fault Detection Optimization Algorithm for Single Event Effect system Based on Multi-information Entropy Fusion

Fault detection caused by single event effect( SEE) in system was studied,and an improved fault detection algorithm by fusing multi-information entropy for detecting soft error was proposed based on multi-objective detection approach and classification management method. In the improved fault detection algorithm, the analysis model of posteriori information with corresponding multi-fault alternative detection points was formulated through correlation information matrix, and the maximum incremental information entropy was chosen as the classification principle for the optimal detection points. A system design example was given to prove the rationality and feasibility of this algorithm.This fault detection algorithm can achieve the purpose of fault detection and resource configuration with high efficiency.

Reduction of Systematic Error in Radiopharmaceutical Activity by Entropy Based Mutual Information

The quality of the radiation dose depends upon the gamma count rate of the radionuclide used. Any reduction in error in the count rate is reflected in the reduction in error in the activity and consequently on the quality of dose. All the efforts so far have been directed only to minimize the random errors in count rate by repetition. In the absence of probability distribution for the systematic errors, we propose to minimize these errors by estimating the upper and lower limits by the technique of determinant in equalities developed by us. Using the algorithm we have developed based on the tech- nique of determinant inequalities and the concept of maximization of mutual information (MI), we show how to process element by element of the covariance matrix to minimize the correlated systematic errors in the count rate of 113 mIn. The element wise processing of covariance matrix is so unique by our technique that it gives experimentalists enough maneuverability to mitigate different factors causing systematic errors in the count rate and consequently the activity of 113 mIn.

Tree-based ecosystem services supply and multifunctionality of church forests and their agricultural matrix near Lake Tana,Ethiopia

Ecosystem services(ES)are the connection between nature and society,and are essential for the well-being of local communities that depend on them.In Ethiopia,church forests and the surrounding agricultural matrix supply numerous ES.However,the ES delivered by both land use types have not yet been assessed simultaneously.Here we surveyed both church forests and their agricultural matrices,aiming to quantify,compare and unravel the drivers underlying tree-based ES supply,density and multifunctionality.We found that almost all church forests and half of the agricultural matrices provided high ES densities.ES multifunctionality was higher in the agricultural matrices,suggesting that people deliberately conserve or plant multifunctional tree species.Furthermore,the supply of all categories of ES was positively correlated with church forest age(p-value<0.001)in the agricultural matrix,while the extent of church forest was positively correlated with the density of all categories ecosystem services score in the church forests(p-value<0.001).Our results can be used to prioritize conservation efforts at sites that provide high levels of ES supply,ES density and ES multifunctionality,and to prioritize restoration efforts at sites with low levels thereof.

期权隐含尾部风险信息的系统性风险预警功能研究

系统性风险预警是防范化解系统性风险的重要举措。期权市场隐含着大量有价值且具前瞻性的信息。本文从上证50ETF期权价格中提取隐含尾部风险信息,检验期权隐含尾部风险信息的系统性风险预警功能。实证结果表明,期权隐含尾部风险信息对我国系统性风险具有显著的预测能力,在控制其他风险预警指标后,结果仍然显著。期权隐含尾部风险信息对不同部门系统性风险的预测能力存在差异,对股票市场风险和债券市场的预测效果最好。将期权隐含尾部风险信息加入传统风险预警指标体系后,能够大幅提升预警指标的预警效果,降低噪声信号比。

基于梯度选择的轻量化差分隐私保护联邦学习

为了应对机器学习过程中可能出现的用户隐私问题,联邦学习作为首个无需用户上传真实数据、仅上传模型更新的协作式在线学习解决方案,已经受到人们的广泛关注与研究。然而,它要求用户在本地训练且上传的模型更新中仍可能包含敏感信息,从而带来了新的隐私保护问题。与此同时,必须在用户本地进行完整训练的特点也使得联邦学习过程中的运算与通信开销问题成为一项挑战,亟需人们建立一种轻量化的联邦学习架构体系。出于进一步的隐私需求考虑,文中使用了带有差分隐私机制的联邦学习框架。另外,首次提出了基于Fisher信息矩阵的Dropout机制——FisherDropout,用于对联邦学习过程中在客户端训练产生梯度更新的每个维度进行优化选择,从而极大地节约运算成本、通信成本以及隐私预算,建立了一种兼具隐私性与轻量化优势的联邦学习框架。在真实世界数据集上的大量实验验证了该方案的有效性。实验结果表明,相比其他联邦学习框架,FisherDropout机制在最好的情况下可以节约76.8%~83.6%的通信开销以及23.0%~26.2%的运算开销,在差分隐私保护中隐私性与可用性的均衡方面同样具有突出优势。

损耗SU(2)和SU(1,1)干涉仪中灵敏度过高估计的研究

基于损耗SU(2)和SU(1,1)干涉仪模型,以干涉仪中的相位估值的为研究方向,在理论上研究了与双参量相位估值相比,进行单参量相位估值的时候存在的高估量子Fisher信息(quantum Fisher information,QFI)的一般表达式;以相干态和压缩真空态输入为例,数值分析了高估QFI随损耗系数或分束比的变化,发现这时出现的高估QFI的消失和恢复现象是和分束比,增益因子以及压缩振幅具有一定的关系.通过调整分束比和损耗系数,可获得最佳的灵敏度,有利于在有损环境下进行量子精密测量.

基于先验信息的压缩感知重建温度场技术

针对利用压缩感知方法重建微处理器芯片温度场存在错失真实热点、从而影响重建精度的问题,提出了一种基于先验信息的压缩感知重建温度场方法。通过对温度场先验信息的处理,结合主成分分析和模拟退火算法有针对性地设计观测矩阵,优化温度传感器的布置,提高重建精度。实验结果表明:与基于特征图的重建方法、基于模拟退火算法布置传感器的方法和基于随机采样的压缩感知重建温度场方法相比,该方法在平均温度误差、最大温度误差和均方误差方面至少分别提升了29.9%、46.6%和53.7%,有更优越的温度场重建性能。

基于FAHP的高职院校教师信息化教学能力综合评价

参考教育部教师工作司“中国高校教师专业发展调研”项目研究成果,从高职教师信息化教学能力应有的内涵出发,建立分析框架,确定相关评价指标的权重;构建模糊系统,采用FAHP分析方法,提出了一套高职教师信息化教学能力综合评价方法,以期为高职院校教师及教学管理人员的信息化能力提升提供参考。

基于快速评价方法的土地利用变化分析

为构建快速评价方法,及时掌握区域土地利用变化动态,促进土地资源的科学合理利用,推进自然资源可持续发展,利用影像自动分割技术,对2010年、2020年两期遥感数据进行地类信息采集,利用ArcGIS模型构建技术,采用土地利用动态变化度、地学信息图谱及土地利用转移矩阵等方法对研究区土地利用情况进行综合分析。结果显示,2010—2020年研究区林地面积增加244.81 hm~2,住宅用地面积增加69.68 hm~2,水域及水利设施用地面积增加33.60 hm~2;耕地和草地面积分别减少262.81 hm~2、30.71 hm~2,其他地类面积变化不大。从土地利用动态变化度来看,公共管理与公共服务用地增幅显著,达到24.62%。从地学信息图谱及土地利用转移矩阵来看,林地增加来源地类主要为耕地、园地及草地,整个研究区域均有分布,主要受到退耕还林政策及在影像分割和目视解译过程中的林下耕地影响。通过一系列研究较快地摸清了土地利用数量、布局及各地类之间相互转化的剧烈程度,可为土地利用可持续发展及相关部门开展研究提供决策依据。

微博平台烟草信息的主题特征及情感倾向分析

目的 了解微博用户发布和公众关注的烟草信息的主题特征,并探究各类烟草信息的传播效果,为推动控烟信息的高效传播及效果提升提供理论参考。方法 使用Python软件爬取微博用户发布的烟草信息,采用UCINET软件进行数据分析和共词矩阵分析。结果 经爬取、筛选后共获得6385条烟草信息。其中,烟草信息的关键词整体呈高异质性、广覆盖特征,其频次以“吸烟”“抽烟”居多;正向情感的烟草信息关键词(68.71%)较负向情感(6.98%)多,其频次以“吸烟”“二手烟”居多。结论 微博平台中烟草信息的网络生态整体较好,烟草相关内容占比较小,但具有较强的诱惑性和隐蔽性。相关部门应持续关注烟草流行词汇,并加强烟草危害和控烟法律的宣传,谨防负向情感的烟草信息传播。

基于mRMR-SOM的异步电机轴承故障诊断研究

针对异步电机轴承故障诊断问题,提出了一种融合最大相关最小冗余特征选择算法(mRMR)和自组织映射神经网络(SOM)的故障诊断方法,并将其应用于轴承故障诊断的不同阶段。首先,在实验室环境下搭建了异步电机故障诊断试验平台,在不同电机状态下分别采集振动、电流和电压信号,利用统计学方法获取了高维混合特征集;然后,以互信息为背景,利用mRMR根据特征与状态标签间的相关性和特征间的冗余性,筛选了具备强区分能力的特征,以避免计算冗余和后验诊断性能下降;最后,采用SOM对异步电机健康和轴承故障状态进行了分类识别,验证了SOM对异步电机轴承故障诊断的有效性,以及mRMR对故障诊断结果的影响。研究结果表明:基于mRMR-SOM的异步电机轴承故障诊断方法能够准确地区分健康和故障状态,测试集分类准确率达到89%;使用mRMR特征筛选能够将154维特征降低至17维,缩短23.5%的网络收敛时间,并将分类准确率由89%提升至98%;试验结果验证了基于mRMR-SOM的异步电机轴承故障诊断方法对于异步电机轴承故障诊断问题的有效性,且证实其具备良好的诊断效果。

结合空时上下文信息的视频SAR图像相干斑滤波

作为合成孔径雷达(synthetic aperture radar,SAR)的一种新体制,视频SAR能够对场景连续成像,在目标检测、跟踪等应用情景有独特优势。然而,相干斑的存在影响了视频SAR图像质量及后续目标检测应用。针对这一问题,提出了一种结合空时上下文信息的视频SAR图像相干斑滤波方法。该方法主要由3步构成:首先构建能表征视频SAR图像距离-方位-时间三维动态散射信息的空时上下文协方差矩阵;其次根据协方差矩阵的相似检验选取一定邻域内目标像素的相似样本;最后根据相似样本进行平均实现相干斑滤波。基于两组实测视频SAR数据开展相干斑滤波对比实验,实验结果表明所提方法能在有效抑制相干斑的同时较好地保留目标细节信息,验证了所提方法的有效性和优势。

密度矩阵泛函理论及其计算方法

随着密度泛函理论的普及,发明人Kohn于1998年获得诺贝尔化学奖.在密度泛函理论中,轨道占有数只取1或者0.Gilbert于1975年提出密度矩阵泛函理论,在这一理论方法中,轨道占有数除了1和0之外,还可以取0至1之间的分数.从形式上看,这一理论推广了密度泛函理论.然而,Gilbert发现当占有数为分数时,轨道能级都是简并的,这与实验观察到的能级结构不符.因为能级简并,无法像密度泛函理论那样获得真正的轨道的本征值方程,计算只能依靠非线性优化方法,计算效率很低.这个近半个世纪的难题,最近被我们攻克.我们用信息熵函数提取密度矩阵泛函理论的关联能,由此获得轨道的自洽场本征值方程,实现密度矩阵泛函理论方法的高效计算.

基于多参信息量的继电保护整定计算系统

为了保证定值数据一致性,实现配电网稳定运行,设计基于多参信息量的继电保护整定计算系统。使用GIS系统按地理位置绘制配电网图形,动态获取多参信息量;构建整定计算模块,使模块元加以调用并组合;设计基于GUI开发图形的人机交互可视化模块,使整定结果以图表形式展示。整合多参信息量为一个定值集,利用导纳矩阵稀疏性,只存储和计算非零元参量。计算正序、负序和零序三个网络下的短路三序电流,并对其进行灵敏度校验,获取整定结果。系统实现对保护整定的可视化显示,并且将整定结果以静态的表格形式呈现。将整定过程中的相关信息以数据柱的形式进行整理,最后将整定的结果以数据库的形式显示出来。实验结果表明,设计系统的整定计算结果精准度最高可达99.06%,表明整定计算结果效果较好。