The objective of this research was to compute the principal matrix square root with sparse approximation. A new stable iterative scheme avoiding fully matrix inversion (SIAI) is provided. The analysis on the sparsity and error of the matrices involved during the iterative process is given. Based on the bandwidth and error analysis, a more efficient algorithm combining the SIAI with the filtering technique is proposed. The high computational efficiency and accuracy of the proposed method are demonstrated by computing the principal square roots of different matrices to reveal its applicability over the existing methods.
翻译:这项研究的目的是以少许近似值计算主矩阵平方根;提供了一个新的稳定的迭代办法,避免完全转换矩阵(SIAI),对迭代过程所涉矩阵的宽度和误差进行了分析;根据带宽和误差分析,提出了将SIAI与过滤技术相结合的更有效的算法;通过计算不同矩阵的主要平方根,以显示其对现有方法的适用性,证明了拟议方法的高计算效率和准确性;通过计算不同矩阵的主要平方根,显示了拟议方法的高计算效率和准确性;通过计算不同矩阵的主要平方根,揭示了对现行方法的适用性。