Iterative Algorithms for Assessing Network Resilience Against Structured Perturbations

This article studies network resilience against structured additive perturbations to its topology. We consider dynamic networks modeled as linear time-invariant systems subject of bounded energy satisfying specific sparsity and entry-wise constraints. Given an level, the pseudospectral abscissa captures worst-possible perturbation adversary could employ destabilize network, stability radius is maximum in that can withstand without becoming unstable. Building on a novel characterization worst-case perturbation, we propose iterative algorithms efficiently compute radius. provide theoretical guarantees local convergence illustrate their efficacy accuracy several examples.