New Paper Accepted in IEEE Signal Processing Letters
Congratulations to R. Money, J. Krishnan (SimulaMet), B. Beferull-Lozano, E. Isufi (Delft University) for the acceptance of a journal paper in IEEE Signal Processing Letters (Early access at IEEE Xplore).
Title: Online Missing Data Imputation of Edge Flows
Short description of the paper:
A novel online algorithm for missing data imputation for networks with signals defined on the edges is presented in this paper. Leveraging the prior knowledge intrinsic to most real world networks, we propose a bi-level optimization scheme that includes: (i) a sparse line graph identification strategy by solving a group-Lasso-based optimization framework via composite objective mirror descent to exploit the causal dependencies among the signals and (ii) a Kalman-filtering-based signal reconstruction strategy developed using simplicial complex (SC) formulation to exploit the flow conservation. To the best of our knowledge, this is the first SC-based attempt for time-varying signal imputation, whose advantages have been demonstrated through numerical experiments conducted using EPANET models of both synthetic and real water distribution networks.