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Dai, Lifang,Liang, Maolin The Korean Society for Computational and Applied M 2013 Journal of applied mathematics & informatics Vol.31 No.3
In this paper, the formulas for calculating the extremal ranks and inertias of the Hermitian least squares solutions to matrix equation AX = B are established. In particular, the necessary and sufficient conditions for the existences of the positive and nonnegative definite solutions to this matrix equation are given. Meanwhile, the least squares problem of the above matrix equation with Hermitian R-symmetric and R-skew symmetric constraints are also investigated.
Lifang Dai,Maolin Liang 한국전산응용수학회 2013 Journal of applied mathematics & informatics Vol.31 No.3
In this paper, the formulas for calculating the extremal ranksand inertias of the Hermitian least squares solutions to matrix equation AX = B are established. In particular, the necessary and sufficient conditionsfor the existences of the positive and nonnegative definite solutionsto this matrix equation are given. Meanwhile, the least squares problemof the above matrix equation with Hermitian R-symmetric and R-skewsymmetric constraints are also investigated.
Mao Lin,Ying-Hui Li,Liang Qu,Chen Wu,Guo-Qiang Yuan 전력전자학회 2016 JOURNAL OF POWER ELECTRONICS Vol.16 No.1
Fault detection is the research focus and priority in this study to ensure the high reliability of a proposed three-level inverter. Kernel principal component analysis (KPCA) has been widely used for feature extraction because of its simplicity. However, highlighting useful information that may be hidden under retained KPCs remains a problem. A weighted KPCA is proposed to overcome this shortcoming. Variable contribution plots are constructed to evaluate the importance of each KPC on the basis of sensitivity analysis theory. Then, different weighting values of KPCs are set to highlight the useful information. The weighted statistics are evaluated comprehensively by using the improved feature eigenvectors. The effectiveness of the proposed method is validated. The diagnosis results of the inverter indicate that the proposed method is superior to conventional KPCA.