论文标题

无逆在线独立矢量分析具有灵活的迭代源转向

Inverse-free Online Independent Vector Analysis with Flexible Iterative Source Steering

论文作者

Nakashima, Taishi, Ono, Nobutaka

论文摘要

在本文中,我们提出了一种新的在线独立矢量分析(IVA)算法,用于实时盲目分离(BSS)。在许多BSS算法中,迭代投影(IP)已用于更新Demixing矩阵,这是BSS中要估计的参数。但是,它需要矩阵倒置,这可能是昂贵的,尤其是在在线处理中。为了改善这种情况,我们将迭代源转向(ISS)引入在线IVA。 ISS不需要任何矩阵倒置,因此其计算复杂性小于IP。此外,当仅部分来源移动时,ISS使我们能够灵活有效地更新矩阵,以便更新移动源的转向向量。在动态条件下的数值实验证实了该方法的功效。

In this paper, we propose a new online independent vector analysis (IVA) algorithm for real-time blind source separation (BSS). In many BSS algorithms, the iterative projection (IP) has been used for updating the demixing matrix, a parameter to be estimated in BSS. However, it requires matrix inversion, which can be costly, particularly in online processing. To improve this situation, we introduce iterative source steering (ISS) to online IVA. ISS does not require any matrix inversions, and thus its computational complexity is less than that of IP. Furthermore, when only part of the sources are moving, ISS enables us to update the demixing matrix flexibly and effectively so that the steering vectors of only the moving sources are updated. Numerical experiments under a dynamic condition confirm the efficacy of the proposed method.

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