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Conjugate gradient least squares algorithm for solving the generalized coupled Sylvester-conjugate matrix equations

机译:用于求解广义耦合Sylvester缀合物矩阵方程的共轭梯度最小二乘算法

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In this study, we consider the minimum-norm least squares solution of the generalized coupled Sylvester-conjugate matrix equations by conjugate gradient least squares algorithm. When the system is consistent, the exact solution can be obtained. When the system is inconsistent, the least squares solution can be obtained within finite iterative steps in the absence of round-offerror for any initial matrices. Furthermore, we can get the minimum-norm least squares solution by choosing special types of initial matrices. Finally, some numerical examples are given to demonstrate the algorithm considered is quite effective in actual computation. (C) 2018 Elsevier Inc. All rights reserved.
机译:在该研究中,我们考虑了通过共轭梯度最小二乘算法考虑广义耦合的Sylvester-缀合物矩阵方程的最小常态最小二乘解。 当系统一致时,可以获得精确的解决方案。 当系统不一致时,可以在没有圆形的循环的情况下在任何初始矩阵的情况下在有限迭代步骤中获得最小二乘解决方案。 此外,我们可以通过选择特殊类型的初始矩阵来获得最小常态最小二乘解。 最后,给出了一些数值例子来证明所考虑的算法在实际计算中非常有效。 (c)2018年Elsevier Inc.保留所有权利。

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