• Corpus ID: 211126870

Sampling Policy Design for Tracking Time-varying Graph Signals with Adaptive Budget Allocation

  title={Sampling Policy Design for Tracking Time-varying Graph Signals with Adaptive Budget Allocation},
  author={Xuan Xie and Hui Feng and Bo Hu},
  journal={2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)},
  • Xuan XieHui FengBo Hu
  • Published 14 February 2020
  • Computer Science
  • 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
There have been many works that focus on the sampling policy design for static graph signals (GS), but few for time-varying GS. In this paper, we concentrate on how to select vertices to sample and how to allocate the sampling budget for a time-varying GS to reduce tracking error. In the Kalman Filter (KF) framework, the problem of sampling policy design and budget allocation is formulated as an infinite horizon sequential decision process, in which the optimal sampling policy is obtained by… 

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