ICASSP 2024accepted0 citations
Joint INDSCAL Decomposition Meets Blind Source Separation
Le Trung Thanh, Karim Abed-Meraim, Philippe Ravier, Olivier Buttelli, Ales Holobar
Abstract
This paper introduces TenSOFO, a novel tensor-based method specifically designed for blind source separation (BSS). Ten-SOFO presents a new efficient alternating direction method of multipliers framework, allowing for simultaneous decomposition of two symmetric third-order tensors under the individual differences in scaling (INDSCAL) format. By establishing a fundamental link between joint INDSCAL decomposition and BSS using second and fourth order statistics, TenSOFO proves to be effective for BSS. The performance of TenSOFO is evaluated in both joint INDSCAL decomposition and BSS tasks, showcasing its remarkable accuracy and potential applications.
BibTeX
@inproceedings{icassp2024_jointindscaldeco,
title = {Joint INDSCAL Decomposition Meets Blind Source Separation},
author = {Le Trung Thanh and Karim Abed-Meraim and Philippe Ravier and Olivier Buttelli and Ales Holobar},
booktitle = {ICASSP 2024},
year = {2024}
}