On constructing orthogonal generalized doubly stochastic matrices

arXiv: Numerical Analysis(2018)

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摘要
A real quadratic matrix is generalized doubly stochastic (g.d.s.) if all of its row sums and column sums equal one. We propose numerically stable methods for generating such matrices having possibly orthogonality property or/and satisfying Yang-Baxter equation (YBE). Additionally, an inverse eigenvalue problem for finding orthogonal generalized doubly stochastic matrices with prescribed eigenvalues is solved here. The tests performed in MATLAB illustrate our proposed algorithms and demonstrate their useful numerical properties.
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