Discussion to the paper “Independent component analysis by robust distance correlation”
Abstract
Abstract In this discussion, we comment on the paper by Leyder et al., which introduces a new framework for robust independent component analysis based on robust distance correlation. Our discussion focuses on the role of whitening, the choice of scatter matrices, and the implications of the independence property in robust ICA. We further argue that the minimum distance index is preferable to the Amari index as a performance measure, as it admits a direct connection to the limiting distribution of ICA estimators. Overall, the paper by Leyder et al. constitutes an important contribution to robust blind source separation and opens several promising avenues for future research.
Fields of Study & Subjects
Blind Source Separation Techniques
Sparse and Compressive Sensing Techniques
Direction-of-Arrival Estimation Techniques
Publication details
- Journal / source
- Advances in Data Analysis and Classification
- Publisher
- Springer Science and Business Media LLC
- Volume
- 20
- Issue
- 3
- Pages
- 789–798
- Publication date
- 25 June 2026
- Language
- EN