Let $G$ be a connected graph and let $T$ spanning tree of $G$. A partial orientation $\sigma$ respect to is an the edges except those $T$, resulting associated with which denoted by $G_T^\sigma$. In this paper we prove that there exists such largest eigenvalue Hermitian adjacency matrix $G_T^\sigma$ at most absolute value roots matching polynomial

The workshop discussed the numerical solution of linear and nonlinear eigenvalue problems for partial differential equations. It included the theoretical analysis the development of new (adaptive) methods, the iterative solution of the algebraic problems as well as the application in many areas of science and engineering. Mathematics Subject Classification (2000): 65N25, 65F15, 15A18. Introduct...

As a supplement or an alternative to classification of hyperspectral image data the linear mixture model is considered in order to obtain estimates of abundance of each class or endmember in pixels with mixed membership. Full unmixing and the partial unmixing methods orthogonal subspace projection (OSP), constrained energy minimization (CEM) and an eigenvalue formulation alternative are dealt w...

Constraint satisfaction problems are combinatorial optimization problems which involve finding an assignment to a set of variables that is consistent with a set of constraints. In this paper the use of two local search techniques, namely GENET and Tabu Search for constraint satisfaction optimization problems and partial constraint satisfaction problems is investigated. These methods are compare...

In this paper we study the partial pole assignment problem for the quadratic pencil by output feedback control where the output matrix is also a designing parameter. In addition, the input matrix is set to be the transpose of the output matrix. Under certain assumption, we give a solution to this partial pole assignment problem in which the unwanted eigenvalues are moved to desired values and a...

We present a new computational approach for a class of large-scale nonlinear eigenvalue problems (NEPs) that are nonlinear in the eigenvalue. The contribution of this paper is two-fold. We derive a new iterative algorithm for NEPs, the tensor infinite Arnoldi method (TIAR), which is applicable to a general class of NEPs, and we show how to specialize the algorithm to a specific NEP: the wavegui...

Finding global optimum of a non-convex quadratic function is in general a very difficult task even when the feasible set is a polyhedron. We show that when the feasible set of a quadratic problem consists of orthogonal matrices from Rn×k, then we can transform it into a semidefinite program in matrices of order kn which has the same optimal value. This opens new possibilities to get good lower ...