一种基于gamma分布的NMF算法及其在人脸识别中的应用

提出了一种基于gamma分布的NMF算法(GNMF),并将之用于人脸特征抽取.构造了特征子空间,并在特征子空间内实现脸部识别.结果表明,GNMF算法可行且有效,以GNMF为基础的人脸识别率较高.     

树上的Markov映射的逆极限

本文针对树T上的Markov映射f,结合f对应的关联矩阵的特点 ,就f的逆极限不可分 ,f的逆极限同胚于树T ,f的逆极限是一拓扑射线R趋于一连续统Y1,f的逆极限含有不可分子连续统这四种情形分别给出一个充分条件 .同时 ,明确指出 3-星形树Y上一类特殊的Markov映射的逆极限 .     

用EPROM简化时序逻辑电路的设计

逻辑线路的设计是比较复杂的,对于初学者来说是一大难点,用EPROM可以简化逻辑设计,本文在文〔1〕的基础上给出简化时序逻辑电路设计的方法。     

矩阵正定性的推广

通过问题的提出,进一步讨论对称矩阵(aij)n×n与(aij)n×n正定性     

广义规范矩阵的Kronecker积

给出了一类重要的矩阵——广义规范矩阵的Kronecker积的一些性质．     

关于矩阵值Lipschitz映射空间的若干研究

引入并研究了由紧的距离空间(K,d)到Mm,n(F)中的Lipschitz-α映射构成的空间Lα(K,Mm,n(F))和lα(K,Mm,n(F));并证明了它们关于范数‖f‖α=‖f‖∞ Lα(f)是Lipschitz空间;得到了lα(K,Mm,n(F))是Lα(K,Mm,n(F))的闭子空间;当0<α≤β≤1时,Lβ(K,Mm,n(F))是Lα(K,Mm,n(F))的闭子空间.     

幂零矩阵性质的一个应用

利用幂零矩阵的特性，给出了求一些特殊矩阵逆矩阵的简单方法。     

Comparison of Inverse Wishart and Separation-Strategy Priors for Bayesian Estimation of Covariance Parameter Matrix in Growth Curve Analysis

Growth curve modeling provides a general framework for analyzing longitudinal data from social, behavioral, and educational sciences. Bayesian methods have been used to estimate growth curve models, in which priors need to be specified for unknown parameters. For the covariance parameter matrix, the inverse Wishart prior is most commonly used due to its proper and conjugate properties. However, many researchers have pointed out that the inverse Wishart prior might not work as expected. The purpose of this study is to investigate the influence of the inverse Wishart prior and compare it with a class of separation-strategy priors on the parameter estimates of growth curve models. In this article, we illustrate the use of different types of priors with 2 real data analyses, and then conduct simulation studies to evaluate and compare these priors in estimating both linear and nonlinear growth curve models. For the linear model, the simulation study shows that both the inverse Wishart and the separation-strategy priors work well for the fixed effects parameters. For the Level 1 residual variance estimate, the separation-strategy prior performs better than the inverse Wishart prior. For the covariance matrix, the results are mixed. Overall, the inverse Wishart prior is suggested if the population correlation coefficient and at least 1 of the 2 marginal variances are large. Otherwise, the separation-strategy prior is preferred. For the nonlinear growth curve model, the separation-strategy priors work better than the inverse Wishart prior.     

加强物理模型教学培养学生创新能力

主要针对目前物理教学实际存在的问题,通过论证物理模型教学与创新思维能力的关系,提出物理模型教学是培养学生创新思维能力的有效途径,并侧重从3个角度论述如何建立物理模型。     

带有时滞的多非线性区间Lurie系统的鲁棒绝对稳定性

讨论了一类带有时滞多非线性区间系统的鲁棒绝对稳定性,通过引入区间矩阵,以及Lyapunov稳定性理论,给出了区间Lurie系统鲁棒绝对稳定性的判别条件,推广了参考文献[5]的结论.