Online optimisation studies the convergence of optimisation methods as the data embedded in the problem changes. Based on this idea, we propose a primal dual online method for nonlinear time-discrete inverse problems. We analyse the method through regret theory and demonstrate its performance in real-time monitoring of moving bodies in a fluid with Electrical Impedance Tomography (EIT). To do so, we also prove the second-order differentiability of the Complete Electrode Model (CEM) solution operator on L∞.
@article{arxiv.2412.12944,
title = {Online optimisation for dynamic electrical impedance tomography},
author = {Neil Dizon and Jyrki Jauhiainen and Tuomo Valkonen},
journal= {arXiv preprint arXiv:2412.12944},
year = {2025}
}