Considerations for robust ICA: a discussion of the PICARD framework
Abstract This study explores the PICARD framework for Independent Component Analysis (ICA), focusing on robust implementation methods. We utilize the "Cocktail party" and handwritten digits datasets to discuss features of the framework's application and performance.
Authors
- Giorgia Zaccaria (ORCID: https://orcid.org/0000-0001-9119-9104)
- Francesca Greselin (ORCID: https://orcid.org/0000-0003-2929-1748)
Institutions
- University of Milano-Bicocca (IT)
Publication Details
- Journal
- Advances in Data Analysis and Classification
- Published
- 2026-06-29
- DOI
- https://doi.org/10.1007/s11634-026-00702-8
- Primary Topic
- Blind Source Separation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Università degli Studi di Milano
- Università degli Studi di Milano-Bicocca