in this paper, an iterative method is proposed for solving the matrix inverse problem $ax=b$ for hermitian-generalized hamiltonian matrices with a submatrix constraint. by this iterative method, for any initial matrix $a_0$, a solution $a^*$ can be obtained in finite iteration steps in the absence of roundoff errors, and the solution with least norm can be obtained by choosing a special kind of...

In this paper, an iterative method is proposed for solving the matrix inverse problem $AX=B$ for Hermitian-generalized Hamiltonian matrices with a submatrix constraint. By this iterative method, for any initial matrix $A_0$, a solution $A^*$ can be obtained in finite iteration steps in the absence of roundoff errors, and the solution with least norm can be obtained by choosing a special kind of...

If a linear program tLP) possesses a large generalized network (G N) submatrix, this structure can be exploited to decrease solution time. The problems of finding maximum sets of GN constraint s and finding maximum embedded GN sub matrices are shown to be NP-complete, indicating that reliable, efficient solution of these problems is difficult. Therefore, efficient heuristic algorithms are devel...

This paper studies the problem of selecting a submatrix of a positive definite matrix in order to achieve a desired bound on the smallest eigenvalue of the submatrix. Maximizing this smallest eigenvalue has applications to selecting input nodes in order to guarantee consensus of networks with negative edges as well as maximizing the convergence rate of distributed systems. We develop a submodul...

By using Moore-Penrose generalized inverse and the general singular value decomposition of matrices, this paper establishes the necessary and sufficient conditions for the existence of and the expressions for the centrosymmetric solutions with a submatrix constraint of matrix inverse problem AX = B. In addition, in the solution set of corresponding problem, the expression of the optimal approxi...

We say that X = [xij ]i,j=1 is symmetric centrosymmetric if xij = xji and xn−j+1,n−i+1, 1 ≤ i, j ≤ n. In this paper we present an efficient algorithm for minimizing ‖AXB + CY D − E‖ where ‖ · ‖ is the Frobenius norm, A ∈ Rt×n, B ∈ Rn×s, C ∈ Rt×m, D ∈ Rm×s, E ∈ Rt×s and X ∈ Rn×n is symmetric centrosymmetric with a specified central submatrix [xij ]r≤i,j≤n−r, Y ∈ Rm×m is symmetric with a specifie...

We present a row-by-row (RBR) method for solving semidefinite programming (SDP) problem based on solving a sequence of problems obtained by restricting the n-dimensional positive semidefinite constraint on the matrix X. By fixing any (n − 1)-dimensional principal submatrix of X and using its (generalized) Schur complement, the positive semidefinite constraint is reduced to a simple second-order...