.png){kind=icon}
返回
Computationally-Efficient Overdetermined Blind Source Separation Based on Iterative Source Steering
.png){kind=icon}
PRE
AI
DOI：10.1109/LSP.2021.3134939.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper describesa computationally-efficient optimization algorithm for the blind source separation (BSS) of overdetermined mixtures. In the determined case, a matrix-inversion-free iterative source steering (ISS) algorithm has been proposed for estimating a square demixing matrix as a computationally-efficient alternative to the popular iterative projection (IP) algorithm. The IP algorithm is based on source-wise (i.e., row-wise) updates of the demixing matrix, and lends itself naturally to an extension to overdetermined independent vector analysis (IVA) called OverIVA. In contrast, the ISS algorithm changes the whole demixing matrix at every update, making its extension to the overdetermined case non-trivial. In this paper, we propose a modified ISS algorithm for OverIVA fully exploiting the computational savings of ISS. We also derive an overdetermined extension of independent low-rank matrix analysis (OverILRMA) with the modified ISS algorithm. Experimental results showed that the proposed ISS-based OverIVA and OverILRMA were comparable or superior to the conventional IP-based counterparts in speech separation performance while achieving lower computational cost.
Keyword:
Signal processing algorithms
IP networks
Iterative algorithms
Blind source separation
Parameter estimation
Microphones
Cost function
Overdetermined blind source separation
independent vector analysis
fast algorithm
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
机构
引用论文
Retrait séculaire des glaciers locaux de montagne : un exemple dans les Alpes occidentales françaises山地局部冰川的世纪性退缩：法国西部阿尔卑斯山的一个例子
OAAI
OAAI分享收藏分享收藏Identification of Critical Components in the Complex Technical Infrastructure of the Large Hadron Collider Using Relief Feature Ranking and Support Vector Machines使用Relief特征排序和Support Vector Machines识别大型强子对撞机复杂技术基础设施中的关键组件.png)
EnergiesOAAI
EnergiesIF0
OAAI分享收藏Tandem Duplications, Segmental Duplications and Deletions, and Their Applications串联重复、片段重复和缺失及其应用
PREAI
分享收藏
查看更多内容