By using the characteristic properties of the anti-Hermitian generalized anti-Hamiltonian matrices, we prove some necessary and sufficient conditions of the solvability for algebra inverse eigenvalue problem of anti-H...By using the characteristic properties of the anti-Hermitian generalized anti-Hamiltonian matrices, we prove some necessary and sufficient conditions of the solvability for algebra inverse eigenvalue problem of anti-Hermitian generalized anti-Hamiltonian matrices, and obtain a general expression of the solution to this problem. By using the properties of the orthogonal projection matrix, we also obtain the expression of the solution to optimal approximate problem of an n× n complex matrix under spectral restriction.展开更多
In this paper, the general calculation formulas of radial matrix elements for relativistic n-dimensional hydrogen atom of spin S=0 are obtained, and the recurrence relation of different power order radial matrix eleme...In this paper, the general calculation formulas of radial matrix elements for relativistic n-dimensional hydrogen atom of spin S=0 are obtained, and the recurrence relation of different power order radial matrix elements are also derived.展开更多
针对基于图的无监督特征选择算法存在挖掘数据内在信息不充分,且易受噪声干扰难以获取更具有判别性特征的问题,提出一种基于广义不相关回归和潜在表示学习的无监督特征选择方法(uncorrelated regression and latent representation for ...针对基于图的无监督特征选择算法存在挖掘数据内在信息不充分,且易受噪声干扰难以获取更具有判别性特征的问题,提出一种基于广义不相关回归和潜在表示学习的无监督特征选择方法(uncorrelated regression and latent representation for unsupervised feature selection,URLUFS)。该方法将非负矩阵分解作用于广义不相关回归模型的投影矩阵,使投影矩阵实现非线性的维数约简并获得特征选择矩阵。在特征选择矩阵的基础上,引入自适应图学习来进一步挖掘数据的局部流形结构,并对特征选择矩阵施加范数约束以保持稀疏性。利用潜在表示对数据样本间的相互关系进行学习,引导回归模型中的伪标签矩阵,从而选择出更具有判别性的特征。在8个公开的数据集上进行了数值对比实验,实验结果表明:基于广义不相关回归和潜在表示学习的无监督特征选择算法明显优于其他8种无监督特征选择算法。展开更多
基金Project(10171031) supported by the National Natural Science Foundation of China
文摘By using the characteristic properties of the anti-Hermitian generalized anti-Hamiltonian matrices, we prove some necessary and sufficient conditions of the solvability for algebra inverse eigenvalue problem of anti-Hermitian generalized anti-Hamiltonian matrices, and obtain a general expression of the solution to this problem. By using the properties of the orthogonal projection matrix, we also obtain the expression of the solution to optimal approximate problem of an n× n complex matrix under spectral restriction.
文摘In this paper, the general calculation formulas of radial matrix elements for relativistic n-dimensional hydrogen atom of spin S=0 are obtained, and the recurrence relation of different power order radial matrix elements are also derived.
文摘针对基于图的无监督特征选择算法存在挖掘数据内在信息不充分,且易受噪声干扰难以获取更具有判别性特征的问题,提出一种基于广义不相关回归和潜在表示学习的无监督特征选择方法(uncorrelated regression and latent representation for unsupervised feature selection,URLUFS)。该方法将非负矩阵分解作用于广义不相关回归模型的投影矩阵,使投影矩阵实现非线性的维数约简并获得特征选择矩阵。在特征选择矩阵的基础上,引入自适应图学习来进一步挖掘数据的局部流形结构,并对特征选择矩阵施加范数约束以保持稀疏性。利用潜在表示对数据样本间的相互关系进行学习,引导回归模型中的伪标签矩阵,从而选择出更具有判别性的特征。在8个公开的数据集上进行了数值对比实验,实验结果表明:基于广义不相关回归和潜在表示学习的无监督特征选择算法明显优于其他8种无监督特征选择算法。
文摘为应对新能源机组随机波动导致的外送断面过载约束复杂多变的问题,提出一种计及新能源特性的自动发电控制(automatic generation control,AGC)断面越限预防和校正控制方法。首先,提出计及新能源特性、涵盖主站-厂站-机组三级架构的AGC断面功率越限控制模型;其次,基于潮流转移比矩阵快速计算N-1故障后线路负载率矩阵,快速评估AGC断面功率越限风险;最后,推导线路N-1故障后负载率相对发电机组出力的灵敏度,明确不同机组功率调节对断面功率的差异化影响,以新能源机组消纳最大、AGC机组调节量最小为控制原则,提出基于线路负载率灵敏度的AGC断面越限校正控制方法。在PSD Power Tools中搭建实际电网仿真算例验证了所提方法的正确性和有效性。
