CDC · 2019

Learning Graph Parameters from Linear Measurements: Fundamental Trade-offs and Application to Electric Grids

Tongxin Li, Lucien Werner, Steven H. Low

IEEE Conference on Decision and Control

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How many measurements are needed to recover a network?

Information theoretic bounds relate measurement requirements to graph complexity and recovery error. A recovery algorithm estimates topology and parameters from linear measurements, with demonstrations on graph families and electrical grid test cases.

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Tongxin Li, Lucien Werner, Steven H. Low. Learning Graph Parameters from Linear Measurements: Fundamental Trade-offs and Application to Electric Grids. IEEE Conference on Decision and Control, 2019. https://doi.org/10.1109/CDC40024.2019.9029949

BibTeX
@inproceedings{tongxin-graph-parameters,
  title = {{Learning Graph Parameters from Linear Measurements: Fundamental Trade-offs and Application to Electric Grids}},
  author = {Tongxin Li and Lucien Werner and Steven H. Low},
  year = {2019},
  booktitle = {IEEE Conference on Decision and Control},
  url = {https://doi.org/10.1109/CDC40024.2019.9029949},
  doi = {10.1109/CDC40024.2019.9029949}
}