基于模糊层次分析的虚拟企业风险评价

在分析虚拟企业风险评价应该考虑的主要因素的基础上,建立了一套适用于虚拟企业风险评价的指标体系,提出了一种基于模糊集合理论与层次分析法相结合的虚拟企业风险评价方法。在多专家指标权重评价的基础上,运用模糊D elph i法对上层准则形成一系列的权重集合,得到三角模糊数表示的准则“重要性”评价。结合以模糊语言变量表示的备选方案偏好等级的“满意度”和下层指标的模糊权重,通过分层结合,得到虚拟企业风险的模糊评分,最后采用重心法和Chang Jing-rong的双系数法对所有方案的三角模糊数进行排序,得到虚拟企业方案综合选择的优先顺序。实例说明了虚拟企业风险评价的具体过程。     

GENERALIZED MULTIVARIATE RIDGE REGRESSION ESTIMATE AND CRITERIA Q(e)FOR CHOOSING MATRIX K

When multicollinearity is present in a set of the regression variables,the leastsquare estimate of the regression coefficient tends to be unstable and it may lead toerroneous inference.In this paper,generalized ridge estimateβ(K)of the regression coefficientβ=vec(B)is considered in multivaiate linear regression model.The MSE of the aboveestimate is less than the MSE of the least square estimate by choosing the ridgeparameter matrix K.Moreover,it is pointed out that the Criterion MSE for choosingmatrix K of generalized ridge estimate has several weaknesses.In order to overcomethese weaknesses,a new family of criteria Q(c)is adpoted which includes the criterionMSE and criterion LS as its special case.The good properties of the criteria Q(c)areproved and discussed from theoretical point of view.The statistical meaning of thescale c is explained and the methods of determining c are also given.     

多元广义岭估计及K值选取的 Q(c)准则

当自变量间存在复共线性时,最小二乘估计就表现出不稳定并可能导致错误的结果.本文采用广义岭估计β(K)来估计多元线性模型的回归系数β=vec(B),通过岭参数K值的选取,可使广义岭估计的均方误差MSE小于最小二乘估计的MSE.指出了广义岭估计中根据MSE准则选取K值存在的主要缺陷,采用了一种选取K值的新准则Q(c),它包含MSE准则和最小二乘LS准则作为特例,从理论上证明和讨论了Q(c)准则的优良性,阐明了c值的统计含义,并给出了确定c值的方法.     

Generalized multivariate ridge regression estimate and criteria q(c) for choosing matrixK

When multicollinearity is present in a set of the regression variables, the least square estimate of the regression coefficient tends to be unstable and it may lead to erroneous inference. In this paper, generalized ridge estimate β(K) of the regression coefficient β =vec(B) is considered in multivaiate linear regression model. The MSE of the above estimate is less than the MSE of the least square estimate by choosing the ridge parameter matrix K. Moreover, it is pointed out that the Criterion MSE for choosing matrix K of generalized ridge estimate has several weaknesses. In order to overcome these weaknesses, a new family of criteria Q(c) is adpoted which includes the criterion MSE and criterion LS as its special case. The good properties of the criteria Q(c) are proved and discussed from theoretical point of view. The statistical meaning of the scale c is explained and the methods of determining c are also given. The projects Supported by Natural Science Foundation of Fujian Province     

The compression LS estimate of regression coefficient in multivariate linear model

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一种采用互补结构的宽阻带共模缺陷地滤波器

为了抑制高速差分信号传输中的共模噪声, 提出了一种基于低成本FR4材料制作的互补型缺陷地结构(defected ground structure, DGS)共模阻带滤波器. 滤波器两边采用对称性酒杯形DGS结构, 中间采用对称伞形DGS结构. 由于这两种DGS 结构互补, 整个滤波器结构紧凑, 可以实现小面积设计目的; 另外, 由于三个DGS结构相邻较近, 相互之间存在互感, 可以通过改变相互之间的距离来调节相互之间的互感, 从而实现宽阻带滤波的目的. 仿真和测试结果表明, 该DGS滤波器的差模信号损耗小, 在抑制共模噪声20 dB条件下其阻带范围为4.8–11.4 GHz, 而且面积仅为10 mm×10 mm. 与周期性DGS结构相比, 本方法在相同共模噪声抑制深度下, 具有占用面积不到30%、阻带宽度增加约50%等优点.