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The design of sampling set (DoS) for bandlimited graph signals (GS) has beenextensively studied in recent years, but few of them exploit the benefits ofthe stochastic prior of GS. In this work, we introduce the optimizationframework for Bayesian DoS of bandlimited GS. We also illustrate how the choiceof different sampling sets affects the estimation error and how the priorknowledge influences the result of DoS compared with the non-Bayesian DoS bythe aid of analyzing Gershgorin discs of error metric matrix. Finally, based onour analysis, we propose a heuristic algorithm for DoS to avoid solving theoptimization problem directly.

Bayesian Design of Sampling Set for Bandlimited Graph Signals