Recovering network topologies via Taylor expansion and compressive sensing

DOI10.1063/1.4916788zbMath1374.34112OpenAlexW2065299852WikidataQ40987079 ScholiaQ40987079MaRDI QIDQ4591646

Jun-an Lu, Chi Guo, Guangjun Li, Juan Liu, Xiao-Qun Wu

Publication date: 17 November 2017

Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1063/1.4916788

Mathematics Subject Classification ID

Nonlinear oscillations and coupled oscillators for ordinary differential equations (34C15) Qualitative investigation and simulation of ordinary differential equation models (34C60)

Related Items (4)

Sparse Bayesian learning for network structure reconstruction based on evolutionary game data ⋮ Reconstruction of network topology using status-time-series data ⋮ Compressive sensing-based topology identification of multilayer networks ⋮ Discovering the topology of complex networks via adaptive estimators

Cites Work

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