In this paper the mathematical definition of the minimum energygeneralized inverse is given and its application for computing eigen-sensitivity isdemonstrated.By comparing it with the others,this paper clarifies the merits of thepresent algorithm.Furthermore,an erroneous relation which is still widely used isrectified. 相似文献
In this paper, sharp upper bounds for the Laplacian spectral radius and the spectral radius of graphs are given, respectively. We show that some known bounds can be obtained from our bounds. For a bipartite graph G, we also present sharp lower bounds for the Laplacian spectral radius and the spectral radius, respectively. 相似文献
This note provides short proof of the representation of a symmetric isotropic 4-tensor in an n-dimensional real Euclidean
space.
This revised version was published online in August 2006 with corrections to the Cover Date. 相似文献
How close are Galerkin eigenvectors to the best approximation available out of the trial subspace? Under a variety of conditions the Galerkin method gives an approximate eigenvector that approaches asymptotically the projection of the exact eigenvector onto the trial subspace--and this occurs more rapidly than the underlying rate of convergence of the approximate eigenvectors. Both orthogonal-Galerkin and Petrov-Galerkin methods are considered here with a special emphasis on nonselfadjoint problems, thus extending earlier studies by Chatelin, Babuska and Osborn, and Knyazev. Consequences for the numerical treatment of elliptic PDEs discretized either with finite element methods or with spectral methods are discussed. New lower bounds to the of a pair of operators are developed as well.