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Based on -like decomposition with column pivoting,
a new and efficient numerical method for solving symmetric matrix inverse
eigenvalue problems is proposed, which is suitable for both the distinct and
multiple eigenvalue cases. A locally quadratic convergence analysis is given.
Some numerical experiments are presented to illustrate our results.
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