Greedy Brain Source Localization with Rank Constraints

Viviana Hernandez-Castañon, Steven Le Cam, Radu Ranta

2025

Abstract

This paper introduces a new low rank matrix approximation model and a greedy algorithm from the iterative regression family to solve it. Unlike the classical Orthogonal Matching Pursuit (OMP) or Orthogonal Least Squares (OLS), the elements of the dictionary are not vectors but matrices. For reconstructing a measurement matrix from this dictionary, the regression coefficients are thus matrices, constrained to be low (unit) rank. The target application is the inverse problem in brain source estimation. On simulated data, the proposed algorithm shows better performances than classical solutions used for solving the mentioned inverse problem.

Paper Citation

in Harvard Style

Hernandez-Castañon V., Le Cam S. and Ranta R. (2025). Greedy Brain Source Localization with Rank Constraints. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS; ISBN 978-989-758-731-3, SciTePress, pages 819-826. DOI: 10.5220/0013386600003911

in Bibtex Style

@conference{biosignals25,
author={Viviana Hernandez-Castañon and Steven Le Cam and Radu Ranta},
title={Greedy Brain Source Localization with Rank Constraints},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS},
year={2025},
pages={819-826},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013386600003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS
TI - Greedy Brain Source Localization with Rank Constraints
SN - 978-989-758-731-3
AU - Hernandez-Castañon V.
AU - Le Cam S.
AU - Ranta R.
PY - 2025
SP - 819
EP - 826
DO - 10.5220/0013386600003911
PB - SciTePress