We analyze a complex matrix inversion algorithm proposed by Frobenius, which we call the Frobenius inversion. We show that the Frobenius inversion uses the least number of real matrix multiplications and inversions among all complex matrix inversion algorithms. We also analyze numerical properties of the Frobenius inversion. We prove that the Frobenius inversion runs faster than the widely used method based on LU decomposition if and only if the ratio of the running time of the real matrix inversion to that of the real matrix multiplication is greater than $5/4$. We corroborate this theoretical result by numerical experiments. Moreover, we apply the Frobenius inversion to matrix sign function, Sylvester equation, and polar decomposition. In each of these examples, the Frobenius inversion is more efficient than inversion via LU-decomposition.
翻译:我们分析Frobenius提出的复杂的矩阵反向算法,我们称之为Frobenius反向演算法,我们称之为Frobenius反向演算法。我们显示,Frobenius反向演算法在所有复杂的矩阵反向演算法中,使用的实际矩阵乘法和反向演算法的数量最少。我们还分析了Frobenius反向演算法的数值属性。我们证明,Frobenius反向演算法比基于LU分解法的广泛使用法要快,如果而且只有在实际矩阵反向与实际矩阵乘法的运行时间比大于5/4美元的情况下。我们通过数字实验证实了这一理论结果。此外,我们用Frobenius反向矩阵签名功能、Sylvester等式和极分解法应用了Frobenius反向演算法。在其中的每一个例子中,Frobenius反向转换都比通过LU-decomposition的转换法更有效。