A time–frequency blind signal separation method applicable to underdetermined mixtures of dependent sources-Reference-Cited by-同舟云学术

A time–frequency blind signal separation method applicable to underdetermined mixtures of dependent sources

Published:2005-07 Issue:7 Volume:85 Page:1389-1403
ISSN:0165-1684
Container-title:Signal Processing
language:en
Short-container-title:Signal Processing

Author:

Abrard Frédéric,Deville Yannick

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference27 articles.

1. Space or time adaptive signal processing by neural network models;Herault,1986

2. Blind separation of sources. Part i;Herault;Signal Processing,1991

3. J. Herault, C. Jutten, B. Ans, Détection de grandeurs primitives dans un message composite pour une architecture de calcul neuromimétique en apprentissage non supervisé, in: GRETSI, Nice, France, May 1985, pp. 1017–1022.

4. J.F. Cardoso, Blind signal separation: statistical principles, in: Proceedings of the IEEE, vol. 86(10), October 1998, pp. 2009–2025.

5. Differential source separation;Deville,2000

Cited by 192 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Joint Underdetermined Blind Separation Using Cross Third-Order Cumulant and Tensor Decomposition;Circuits, Systems, and Signal Processing;2024-07-04

2. Anechoic Demixing under Phase Wraparound Conditions in Assisted Living Environments;2024 35th Irish Signals and Systems Conference (ISSC);2024-06-13

3. Exploiting Time–Frequency Sparsity for Dual-Sensor Blind Source Separation;Electronics;2024-03-26

4. Underdetermined blind source separation based on third‐order cumulant and tensor compression;IET Radar, Sonar & Navigation;2024-03-22

5. Quantifying Non-linear Dependencies in Blind Source Separation of Power System Signals using Copula Statistics;2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT);2024-02-19