A Compressive Sensing Based Analysis of Anomalies in Generalized Linear Models

In this article, we present a compressive sensing based framework for generalized linear model regression that employs a two-component noise model and convex optimization techniques to simultaneously detect outliers and determine optimally sparse representations of noisy data from arbitrary sets of basis functions. We then extend our model to include model order reduction capabilities that can uncover inherent sparsity in regression coefficients and achieve simple, superior fits. Second, we use the mixed ?₂/?₁ norm to develop another model that can efficiently uncover block-sparsity in regression coefficients. By performing model order reduction over all independent variables and basis functions, our algorithms successfully deemphasize the effect of independent variables that become uncorrelated with dependent variables. This desirable property has various applications in real-time anomaly detection, such as faulty sensor detection and sensor jamming in wireless sensor networks. After developing our framework and inheriting a stable recovery theorem from compressive sensing theory, we present two simulation studies on sparse or block-sparse problems that demonstrate the superior performance of our algorithms with respect to (1) classic outlier-invariant regression techniques like least absolute value and iteratively reweighted least-squares and (2) classic sparse-regularized regression techniques like LASSO.     

考虑柔性和间隙的螺旋引纬机构仿真分析

为了提高引纬机构的稳定性和精度,将柔性构件和间隙的影响考虑在内,联合ANSYS和ADAMS建立螺旋引纬机构的刚柔耦合模型,通过ADAMS进行动力学仿真,在刚性系统和刚柔耦合系统中分别分析了旋转铰间隙对剑杆输出特性曲线的影响。在对仿真数据的观察中发现了相当比例的噪声信号,为了消除噪声信号的影响,利用统计学中上下四分位数和中位数来识别替换异常值;在综合考虑间隙和柔性构件的影响时,利用减噪后的加速度曲线与理想刚体系统下的数据的偏差值得到一个新的曲线,该曲线在固定区间内做高频波动,呈现出类似周期性声波信号的特点。结果表明旋转铰间隙是影响剑杆稳定性和精度的主要因素,柔性构件和间隙的综合作用产生了趋向于周期性的碰撞影响。依据研 究结果可以进一步对原刚体模型下设计的引纬机构进行优化设计。     

光PPM取样信号的最大似然解调

研究了光脉冲位置调制全数字接收机的取样信号的最大似然解调及其性能．对接收到的任意脉冲波形给出了解调算法和差错概率上界。以此为基础,对容易实现的最大累加计数判决算法,讨论了各种参数对其解调性能的影响,其结果对设计和实现全数字ＰＰＭ接收机是有益的。     

同态滤波在扭矩载荷识别中的应用

通过理论分析和实验验证,证明了采用同态滤波的方法识别机器扭矩载荷的可行性。同时提出了根据时序模型的Ｇｒｅｅｎ函数来判定窗函数宽度的方法,减少了选取窗函数宽度的盲目性。作为应用实例,给出了采煤机扭矩的识别结果。     

纳西族东巴文献整理范式检析

“以文学为取向”与“以历史主义为取向”构成了东巴文献整理的主要范式,二者彼此消长,又相互交叉。前者把东巴文献视为与作家文学相对的“民间文学”或“口头文学”,通过去宗教化、去仪式化改造以后成了可以为新时代服务的“大众文学”;“以历史主义为取向”则着重于文献产生、发展演变、衰落消亡等一些历史主义倾向的假设命题,在搜集、翻译、整理过程中以意识形态的观点来代替科学研究。     

Modeling of Acoustic Signal Energies with a Generalized Frank Copula. A Linguistic Conjecture is Reviewed

In this article a generalized Frank copula was selected to model the dependence between the energy on two frequency bands of the speech signal, coming from eight languages. An algorithm was developed that uses maximum likelihood to choose the best fitting copula’s parameters. Through bootstrap, the algorithm estimates the variability of the parameters for each language and also computes confidence regions by means of Voronoi tesselations. A linguistic conjecture which claims that the languages are organized in three rhythmic classes, was confirmed by the Voronoi regions. Modeling with a uniparametric Frank copula, the different degrees of dependence between the energies were quantified.     

基于马克思工资决定理论剖析薪酬不公及其分选效应

针对中国就业压力持续增加和结构性用工短缺并存的问题,基于马克思的工资决定理论,从薪酬决定与企业利润、劳动力维持和延续、物价水平以及劳动力市场供求等多个关系角度,分析了我国社会薪酬不公平问题及其所造成的分选效应。在此基础上,针对"求职难、招人难"现象,提出相关建议和对策,旨在缩小薪酬差距,减轻社会就业压力,促进就业结构的和谐,提高人力资源利用效率。     

道德约束环境下的Nash实施

探讨了代理人发送信号的成本对社会选择规则可实施性的影响,证明了在存在道德约束的实施环境中,单调性不再是一个社会选择规则可Nash实施的必要条件。当代理人数量大于2时,满足一致性条件的社会选择规则都是可Nash实施的。当代理人数量等于2,满足交叉性条件和一致性条件的社会选择规则是可Nash实施的。结论表明:在实际的实施问题中,社会选择规则可实施的范围可能远远大于预期,在存在道德约束的实施环境中,一些不满足单调性但却满足一致性条件的社会选择规则,如Pareto规则都是可Nash实施的。     

基于融合熵特征的辐射源信号识别

针对相近雷达辐射源信号难以识别的问题,一种新的雷达辐射源信号识别方法被提出.该方法基于小波包分解,用主成分分析法融合含有信号类别特性的小波包重构系数特征,并将融合特征的能量熵和概率熵构成特征向量,基于支持向量机实现信号的分类识别.在较大信噪比(SNR)范围内,使用该方法能获得满意的正确识别率,当SNR为5 dB时,十分近似的线性调频信号正确识别率达到了91%,实验结果证实了该方法的有效性.