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Impact of source model matrix conditioning on PEVD algorithms

机译:源模型矩阵条件对PEVD算法的影响

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Polynomial parahermitian matrices can accurately and elegantly capture the space-time covariance in broadband array problems. To factorise such matrices, a number of polynomial EVD (PEVD) algorithms have been suggested. At every step, these algorithms move various amounts of off-diagonal energy onto the diagonal, to eventually reach an approximate diagonalisation. In practical experiments, we have found that the relative performance of these algorithms depends quite significantly on the type of parahermitian matrix that is to be factorised. This paper aims to explore this performance space, and to provide some insight into the characteristics of PEVD algorithms.
机译:多项式准herherian矩阵可以准确而优雅地捕获宽带阵列问题中的时空协方差。为了分解这样的矩阵,已经提出了许多多项式EVD(PEVD)算法。在每一步中,这些算法都会将各种不同量的非对角线能量移动到对角线上,最终达到近似的对角化。在实际实验中,我们发现这些算法的相对性能在很大程度上取决于要分解的准herheritian矩阵的类型。本文旨在探索这种性能空间,并提供对PEVD算法特征的一些见解。

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