An Improved GraDe Method for Blind Separation of Graph Signals

被引：2

作者：

Sadeghi, Mohammad ^{[1
]}

Babaie-Zadeh, Massoud ^{[1
]}

机构：

[1] Sharif Univ Technol, Dept Elect Engn, Tehran 1458889694, Iran

来源：

IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2023年 / 71卷

关键词：

Index Terms-Graph signal processing; graph decorrelation; blind source separation; FMRI DATA; ALGORITHM;

D O I：

10.1109/TSP.2023.3331264

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

For blind source separation (BSS) of Gaussian graph signals, an algorithm called GraDe (graph decorrelation) has been previously introduced. In the current paper, it is shown that GraDe does not achieve a good performance for some types of graphs. This is attributed to the estimation of covariance/autocovariance matrices using signal samples, which may not be reliable. To address this weakness, an improvement based on the spectral representation of the signals is proposed, focusing on removing the impact of the outlier eigenvalues. Numerical simulations show that the proposed method outperforms the original GraDe algorithm.

引用

页码：4382 / 4391

页数：10

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