非线性算子方程变号解的存在性与多解性及其应用

利用Banach空间中的锥理论和不动点理论讨论了非线性算子方程变号解的存在性和多解性,通过一个上解给出了非线性算子方程变号解的存在性定理,进而又在一个上解和一个下解的条件下得到了四解存在定理,同时还针对一种重要的非线性算子方程即一类Sturm-Liouville两点边值问题,具体讨论了其变号解的存在性及四解的存在性,相应得到了变号解存在定理和四解存在定理.最后通过一个具体的例子给出定理的应用.     

退化时滞微分方程的特征根

通过研究退化时滞微分方程E.x(t) Ax(t) Bx(t-τ) C.x(t-τ)=0,t≥0的特征根数目,其中rankE=q0是时滞,detC≠0,(E,A)正则.结论是前述方程只有有限个特征根.     

求解大型特征值问题的块Davidson方法的精化技术

块Davidson方法是求解大型对称矩阵特征值问题的一种有效的方法.但对一些特征值问题,当Ritz值收敛以后,该方法并不能保证Ritz向量也同时收敛.因此,为加速块Davidson方法的收敛性,研究了块Davidson方法的重新开始技术,提出了精化块Davidson方法,并对精化块Davidson方法进行了收敛性分析.数值试验和理论分析均表明,新方法对计算大型对称矩阵的一些极端特征对是有效的.     

一类具有不同Virasoro-向量的顶点算子子代数

根据X_I型Cartan矩阵的一类主子矩阵_J,构造出无扭仿射李代数■的同构于g(A_J)的子代数■_J的导代数■_J,以及■_J-模V_■(l,0).证明了V_■(l,0)不仅是顶点算子代数.而且是V_■(l,0)的具有不同Virasoro-向量的顶点算子子代数.     

谢邦杰教授对体上矩阵理论研究的贡献及其在中国的进展

注意到体上矩阵研究的价值与困难,综述了谢邦杰教授1978-1982年关于体上矩阵相似标准形、弱标准形刻画定理,可中心矩阵的特征值基础、行列式方案,以及自共轭四元数矩阵的行列式理论等研究成果;进而阐述了1980年以来中国学者在这些成果基础上对体上矩阵的秩、相似标准形理论、四元数矩阵行列式、自共轭四元数矩阵,以及体上矩阵方程与广义逆矩阵等研究的进一步推进。     

Whence the eigenstate–eigenvalue link?

David Wallace has recently argued that the eigenstate–eigenvalue (E–E) link has no place in serious discussions of quantum mechanics on the grounds that, as he claims, the E–E link is an invention of philosophers rather than the community of practicing physicists. This raises an historical question regarding the origin of the link. This paper aims to answer this question by tracing the historical development of the link through six key textbooks of quantum mechanics. In light of the historical evidence from these textbooks, it is argued that Wallace provides insufficient grounds for dismissing the E–E link from discussions of quantum mechanics.     

一类奇异鞍点问题的特征值界

鞍点问题在最优化理论和方法、计算流体力学等领域具有重要应用.通过巧妙地利用SVD(奇异值分解),讨论了一类奇异鞍点问题的特征值分布,给出了特征值的分布区间估计,推广了T.Rusten和R.Winther的结果.     

Cooperative Sensor Anomaly Detection Using Global Information

Sensor networks are deployed in many application areas nowadays ranging from environment monitoring, industrial monitoring, and agriculture monitoring to military battlefield sensing. The accuracy of sensor readings is without a doubt one of the most important measures to evaluate the quality of a sensor and its network. Therefore, this work is motivated to propose approaches that can detect and repair erroneous (i.e., dirty) data caused by inevitable system problems involving various hardware and software components of sensor networks. As information about a single event of interest in a sensor network is usually reflected in multiple measurement points, the inconsistency among multiple sensor measurements serves as an indicator for data quality problem. The focus of this paper is thus to study methods that can effectively detect and identify erroneous data among inconsistent observations based on the inherent structure of various sensor measurement series from a group of sensors. Particularly, we present three models to characterize the inherent data structures among sensor measurement traces and then apply these models individually to guide the error detection of a sensor network. First, we propose a multivariate Gaussian model which explores the correlated data changes of a group of sensors. Second, we present a Principal Component Analysis (PCA) model which captures the sparse geometric relationship among sensors in a network. The PCA model is motivated by the fact that not all sensor networks have clustered sensor deployment and clear data correlation structure. Further, if the sensor data show non-linear characteristic, a traditional PCA model can not capture the data attributes properly. Therefore, we propose a third model which utilizes kernel functions to map the original data into a high dimensional feature space and then apply PCA model on the mapped linearized data. All these three models serve the purpose of capturing the underlying phenomenon of a sensor network from its global view, and then guide the error detection to discover any anomaly observations. We conducted simulations for each of the proposed models, and evaluated the performance by deriving the Receiver Operating Characteristic (ROC) curves.     

一个供应链系统的可靠性模型的解的渐近性质

运用C0-半群理论来研究一个供应链系统可靠性模型当μi(x)=μi时的解的渐近性质。首先证明在虚轴上除了0之外其他所有点都属于该算子的豫解集,其次证明0是对于该系统的主算子及其共轭算子的几何重数和代数重数为1的特征值,由此推出该系统的时间依赖解当时间趋向于无穷时强收敛于系统的稳态解。     

图谱理论中一些定理的新证明

利用非负矩阵理论并结合图论性质,给出图谱理论中3个重要定理的证明,给出的证明方法比之前文献的证明更为简洁、易懂.