论文标题
双重非平稳性：从非组织混合物中盲目提取独立的非组织矢量/组件 - 算法
Double Nonstationarity: Blind Extraction of Independent Nonstationary Vector/Component from Nonstationary Mixtures -- Algorithms
论文作者
论文摘要
在本文中，将非组织混合和源模型组合在一起，以开发用于独立组件或矢量提取（ICE/IVE）的新的快速准确算法，其中一种代表了众所周知的Fastica的新扩展。该模型允许移动的利益源（SOI），其短间隔的分布可以是（非）圆形（非）高斯。假设提出了一个特定的高斯源模型，假设提出了三对角协方差矩阵结构。证明它在频域扬声器提取问题中是有益的。在模拟中验证了算法。与最先进的算法相比，它们在收敛速度和提取准确性方面表现出卓越的性能。
In this article, nonstationary mixing and source models are combined for developing new fast and accurate algorithms for Independent Component or Vector Extraction (ICE/IVE), one of which stands for a new extension of the well-known FastICA. This model allows for a moving source-of-interest (SOI) whose distribution on short intervals can be (non-)circular (non-)Gaussian. A particular Gaussian source model assuming tridiagonal covariance matrix structures is proposed. It is shown to be beneficial in the frequency-domain speaker extraction problem. The algorithms are verified in simulations. In comparison to the state-of-the-art algorithms, they show superior performance in terms of convergence speed and extraction accuracy.
