基于数字水印的网络控制系统回放攻击检测

随着网络技术在控制系统中的广泛应用,如何处理数据回放及数据篡改等网络攻击行为是广大科技工作者必须考虑和解决的一个问题.在构建包含控制网络和检测网络的控制系统基础上,本文给出了一种网络控制系统的数学模型,并详细阐述了其传感器节点到控制器节点的数据传输方法.考虑到控制器节点遭受回放攻击的实际情况,通过数据帧中添加时间戳和水印数据,并采用拟合优度检验等相关策略,由此提出一种新的异常行为检测方法.仿真结果表明,该方法在一定程度上能够有效并快速地检测出针对控制器的回放攻击行为,具有应用前景和推广参考价值.     

在线网络游戏数据流的建模

针对各种各样的网络游戏,提出了一种网络游戏数据流的建模方法,用该方法建立的数学分布模型可以描述同一类网络游戏产生的数据流的特征.为了衡量数据流和分布模型的吻合度,引入了λ2偏差度量法.最后,以两款流行的网络游戏为例,阐述了建模方法的一般步骤.这两款网络游戏数据包大小和间隔分布模型的偏差度量结果表明建模方法的可行性.     

Statistical models for word frequency distributions: A linguistic evaluation

Three models for word frequency distributions, the lognormal law, the generalized inverse Gauss-Poisson law and the extended generalized Zipf's law are compared and evaluated with respect to goodness of fit and rationale. Application of these models to frequency distributions of a text, a corpus and morphological data reveals that no model can lay claim to exclusive validity, while inspection of the extrapolated theoretical vocabulary sizes raises doubts as to whether the urn scheme with independent trials is the correct underlying model for word frequency data. The role of morphology in shaping word frequency distributions is discussed, as well as parallelisms between vocabulary richness in literary studies and morphological productivity in linguistics.R. Harald Baayen received his PhD at the Free University, Amsterdam, where he was involved in research on morphological productivity. He is now at the Max-Planck Institute for Psycholinguistics, Nijmegen, participating in a project on computational modelling of lexical representation and process.     

飞机航段油耗区间估计最小样本量分析

为解决基于QAR数据进行固定机型固定航段油耗区间估计时如何确定QAR数据样本量的问题,提出一种飞机航段油耗区间估计最小样本量的求解及检验方法。根据固定机型固定航段油耗样本满足N(μ,σ2)正态分布,在满足给定估计精度和显著水平的条件下,推导航段油耗区间估计应满足的最小样本量,利用χ2拟合检验法对最小样本量进行验证,得到最小样本量成立的最小概率要求。通过实例验证了该方法的有效性,为航空公司进行固定机型固定航段油耗估算提供了可行的参考方法。     

基于卡方拟合优度检验的序列等概性测试组

等概性是随机性中的一个重要特性,频数检验是最常见的等概性检验方法.分析了传统频数检验的片面性,利用卡方拟合优度检验提出了全面进行等概性检验的测试组,分别是码元频数检验、等长子序列频数检验和检验结果数据频数检验.使用测试组对国际上常用的随机样本的二进制展开序列进行检验,实验结果表明,该测试组具有较强的等概性检验能力.     

经验分布函数概率模型的分布估计算法

连续域分布估计算法普遍采用高斯概率模型;假设变量服从高斯分布。该假设并不具有普遍意义。提出一个任意分布的连续多变量耦合分布估计算法;利用经验分布函数从样本估计分布;采样产生新的个体。描述经验分布函数和逆变换法采样;讨论用样本构造经验分布函数并采样的基本思想;给出一次采样算法及完整的分布估计算法;通过典型函数的仿真实验;说明方法的正确性和有效性。
     

基于Fisher信息的室内主动SLAM

针对传统的视觉同步定位与地图创建（visual simultaneous localization and mapping,VSLAM）算法在室内弱纹理场景中容易因为特征缺失而定位失败的问题,提出了一种基于最大Fisher信息量云台控制的主动SLAM算法。该方法在经典的ORB-SLAM2框架上进行扩展,增加了Fisher信息场构建模块与云台控制模块。在视觉跟踪的同时,将三维空间划分成若干个体素,根据特征点的空间位置分布更新每个体素的Fisher信息,完成Fisher信息场的构建;当相机获取的图像遇到特征缺失的情况,先找到离相机光心欧式距离最近的体素,以该体素Fisher信息量最大的方向作为相机此时的最优观测方向;计算出坐标变换后相机的偏转角度,通过机载云台实现相机转动到最优观测方向,重新获得场景特征,使得算法在丢失特征之后能够实现自主重定位。将改进后的算法运用到四旋翼无人机仿真平台,结果表明在传统算法失效的情况下,所提算法仍能实时准确地估计无人机位姿,提高了系统的鲁棒性。     

面向建模误差PDF形状与趋势拟合优度的动态过程优化建模

本文提出一种新的数据驱动建模思路及方法, 即面向建模误差概率密度函数(Probability density function, PDF)形状与趋势拟合优度(相似度)的动态过程多目标优化建模方法. 首先, 针对均方根误差(Root mean square error, RMSE)等常规一维性能指标不能完全刻画建模误差在时间和空间二维随机动态特性的问题, 引入PDF指标来对动态过程的建模误差在时间和空间进行二维尺度的全面刻画和评价, 并采用核密度估计技术对关于时间的建模误差序列的PDF进行估计; 其次, 为了刻画动态过程数据建模的拟合趋势, 进一步引入趋势拟合优度指标, 从而构造综合描述数据建模误差PDF形状与趋势拟合相似性的多目标性能指标; 在此基础上, 采用NSGA-II算法优化数据模型的参数集, 获取一大类满足上述多目标性能优化的智能模型参数解. 数值仿真及工业数据验证表明, 所提方法的建模误差PDF逼近设定的期望PDF, 并且模型输出与样本数据拟合趋势接近, 好于常规最小化一维RMSE指标的数据建模方法.     

Robust distributed maximum likelihood estimation with dependent quantized data

In this paper, we consider the distributed maximum likelihood estimation (MLE) with dependent quantized data under the assumption that the structure of the joint probability density function (pdf) is known, but it contains unknown deterministic parameters. The parameters may include different vector parameters corresponding to marginal pdfs and parameters that describe the dependence of observations across sensors. Since MLE with a single quantizer is sensitive to the choice of thresholds due to the uncertainty of pdf, we concentrate on MLE with multiple groups of quantizers (which can be determined by the use of prior information or some heuristic approaches) to fend off against the risk of a poor/outlier quantizer. The asymptotic efficiency of the MLE scheme with multiple quantizers is proved under some regularity conditions and the asymptotic variance is derived to be the inverse of a weighted linear combination of Fisher information matrices based on multiple different quantizers which can be used to show the robustness of our approach. As an illustrative example, we consider an estimation problem with a bivariate non-Gaussian pdf that has applications in distributed constant false alarm rate (CFAR) detection systems. Simulations show the robustness of the proposed MLE scheme especially when the number of quantized measurements is small.     

The reconstruction of a time-dependent source from a surface measurement for full Maxwell’s equations by means of the potential field method

This paper is devoted to the study of an inverse source problem governed by full Maxwell’s equations by means of the potential field method (the $\mathit{A}$-$?$ method). The source term is assumed to be separable in time and space, in which the unknown part is solely time-dependent and is recovered from a surface measurement. We prove that the solution to the inverse problem based on the $\mathit{A}$-$?$ formulation is existing and unique. We suggest a constructive scheme for approximating the solution and discuss its convergence. Finally, a few examples are presented to verify the theoretical results.     

Fisher’s decision tree

Univariate decision trees are classifiers currently used in many data mining applications. This classifier discovers partitions in the input space via hyperplanes that are orthogonal to the axes of attributes, producing a model that can be understood by human experts. One disadvantage of univariate decision trees is that they produce complex and inaccurate models when decision boundaries are not orthogonal to axes. In this paper we introduce the Fisher’s Tree, it is a classifier that takes advantage of dimensionality reduction of Fisher’s linear discriminant and uses the decomposition strategy of decision trees, to come up with an oblique decision tree. Our proposal generates an artificial attribute that is used to split the data in a recursive way.The Fisher’s decision tree induces oblique trees whose accuracy, size, number of leaves and training time are competitive with respect to other decision trees reported in the literature. We use more than ten public available data sets to demonstrate the effectiveness of our method.     

一个无线传感器网络的网络分割模型

首先指出网络分割会影响网络连通性,并进而影响网络的通信效率;接着从物理层和MAC协议入手,讨论了导致无线传感器网络网络分割问题的通信因素。为了定量地刻画网络分割,定义了网络分割比,并分析了影响网络分割比的物理及几何因素。通过试验采集的大量数据及曲线族拟合法,建立了一个无线传感器网络的网络分割模型,定量地确定了网络节点数、面积比与网络分割比的数学关系。