迭代Tikhonov正则化的正则化子及其应用

应用紧算子的奇异系统给出了迭代Tikhonov正则化子．选验选取则参数证明了迭代Tikhonov正则解具有最优的渐近收敛阶。     

基于时域正则化共空间模式的单次脑电情绪识别(英文)

通过使用单次提取脑电信号的分类技术进行情绪词的脑电(EEG)识别研究.以中文情绪双字词为实验材料,通过其诱发的EEG信号,对正性词与中性词、负性词与中性词分别进行分类.使用时域正则化的共空间模式对单次提取脑电信号进行特征提取,并利用线性判别分析方法进行特征分类,分类准确率集中于55%~65%.置换检验验证了实验分类准确率的统计学显著性,表明了情绪词和中性词的成功识别,也有效地证实了基于脑电信号的语言情绪信息的可识别性.此外,在15名被试中,10名被试的负性词与中性词识别率显著,而仅有4名被试的正性词与中性词识别率显著,说明负性情绪更易被识别.     

裁量基准过度规则化的治理——赋予行政执法者个案情况考虑义务

基于行政自制的理念,裁量基准作为控制行政裁量权的一种机制受到理论界和实务界的重视。裁量基准通常采用细化情节和格次效果的形式,但是这种规则的细化可能会导致裁量基准的僵化。要实现个案正义,还必须赋予行政执法人员个案情况考虑义务。     

Regularized Structural Equation Modeling

A new method is proposed that extends the use of regularization in both lasso and ridge regression to structural equation models. The method is termed regularized structural equation modeling (RegSEM). RegSEM penalizes specific parameters in structural equation models, with the goal of creating easier to understand and simpler models. Although regularization has gained wide adoption in regression, very little has transferred to models with latent variables. By adding penalties to specific parameters in a structural equation model, researchers have a high level of flexibility in reducing model complexity, overcoming poor fitting models, and the creation of models that are more likely to generalize to new samples. The proposed method was evaluated through a simulation study, two illustrative examples involving a measurement model, and one empirical example involving the structural part of the model to demonstrate RegSEM’s utility.     

一种数值微分方法

探讨一种求解数值微分的正则化方法,并讨论了它在特殊条件下的收敛性.这种方法结合正则化参数的选取得到了好的收敛阶.     

电阻抗图象重建的新正则化方法

Image reconstruction in elecrical impedance tomography(EIT)is a highly ill-posed inverse problem,Regularization techniques must be used in order to solve the problem,In this paper,a new regularization method based on the spatial filtering theory is proposed.The new regularized reconstruction for EIT is independent of the estimation of impedance distribution,so it can be implemented more easily than the maxiumum a posteriori(MAP) method.The regularization level in our proposed method varies spatially so as to be suited to the correlation character of the object‘s impedance distribution.We implemented our regularization method with two dimensional computer simulations.The experimental results indicate that the quality of the reconstructed impedance images with the descibed regularization method based on spatial filtering theory is better than that with Tikhonov method.     

B值狄里克莱级数下级的进一步探讨

主要利用凸正规化方法进一步探讨了B-值狄里克莱级数的下级，用指数和系数对数的范数的凸正规化序列表示了下级的计算公式。     

带误差的Halpern公开问题的迭代逼近

本文在更一般条件下研究了Halpern公开问题,既把Halpern迭代序列推广到具有误差的迭代序列,同时又把条件非扩张推广到渐近非扩张.从而推广和改进了Halpern公开问题的相应结果.     

迭代逼近Banach空间中强增生算子方程的解

引入和研究了Banach空间中具随机混合型误差的Ishikawa和Mann迭代序列强收敛于强增生算子方程的解的问题,统一、改进和推广了有关文献中的相应结果。     

通过数值分析计算三角形螺绕管电位分布

本文采用数值分析中的有限差分迭代法分别计算了等腰三角形、等边三角形两类通电螺绕管的空间电位分布,该结果可以为设计三角形螺绕管提供必要参考.