共轭矩阵的限制更新顺序矩阵对角化

Fraser K. Coutts, K. Thompson, I. Proudler, Stephan Weiss
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引用次数: 5

摘要

介绍了一些能够迭代计算多项式矩阵特征值分解(PEVD)的算法。PEVD是将普通EVD扩展到多项式矩阵,并将使用拟合运算对角化拟合矩阵。针对序列矩阵对角化(SMD) PEVD算法,提出了一种新的限制更新方法,该方法可以在对算法精度和收敛性影响最小的情况下实现。研究表明,采用本文提出的受限更新SMD (RU-SMD)算法代替SMD算法,可以显著降低PEVD的复杂度和执行时间。这种减少影响了许多宽带多通道问题。
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Restricted update sequential matrix diagonalisation for parahermitian matrices
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is an extension of the ordinary EVD to polynomial matrices and will diagonalise a parahermitian matrix using paraunitary operations. This paper introduces a novel restricted update approach for the sequential matrix diagonalisation (SMD) PEVD algorithm, which can be implemented with minimal impact on algorithm accuracy and convergence. We demonstrate that by using the proposed restricted update SMD (RU-SMD) algorithm instead of SMD, PEVD complexity and execution time can be significantly reduced. This reduction impacts on a number of broadband multichannel problems.
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