Analysis of Consensus Networks Driven by Symmetric-$\alpha$-Stable Motion

This manuscript discusses consensus seeking networks in the presence of non-Gaussian stochastic noise. We explore the fundamental principles of the solutions of the systems and we define performance measures similar to the ones used in the case of Gaussian stochastic noise. We outline the technical difficulties for the exact calculation of these measures and we propose estimates. It is argued that the conventional design tools in optimal network synthesis become obsolete, when the stochastic source of perturbation is not Gaussian.

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