The generalized conjugate direction method for solving quadratic inverse eigenvalue problems over generalized skew Hamiltonian matrices with a submatrix constraint

The generalized conjugate direction method for solving quadratic inverse eigenvalue problems over generalized skew Hamiltonian matrices with a submatrix constraint

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In this paper, we consider a class of constrained quadratic inverse eigenvalue Problem 1.1.Then, a Baby Shirts generalized conjugate direction method is proposed to obtain the generalized skew Hamiltonian matrix solutions with a submatrix constraint.In addition, by Bowls choosing a special kind of initial matrices, it is shown that the unique least Frobenius norm solutions can be obtained consequently.Some numerical results are reported to demonstrate the efficiency of our algorithm.