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February 5, 20260 citations

An improved method for identifying topology of higher-order network

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ZWZhaoyan Wu

Key Points

  • The aim is to identify the unknown topology of higher-order networks effectively.
  • Developed adaptive feedback controllers for network interaction estimation
  • Designed parameter updating laws to adaptively refine estimators
  • Utilized Lyapunov function method and Barbalat's Lemma for analytic proofs
  • Reduced the number of updating laws due to the undirected property
  • Identification efficiency improved significantly in numerical examples
  • Estimators proved effective for a broader range of higher-order networks

Abstract

A higher-order undirected network with both pairwise interactions and group ones among three individuals is considered in this paper. The interactions are represented by topology and assumed to be unknown. Through developing proper adaptive feedback controllers and parameter updating laws, the corresponding network estimators are designed to estimate the unknown topology. The analytic proofs are provided according to Lyapunov function method and Barbalat's Lemma. One thing is noted, that the number of updating laws are greatly reduced in view of the undirected property. Numerical examples show that the identification efficiency is greatly improved. Moreover, the estimators are valid for a wider range of higher-order networks.

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Zhaoyan Wu (2025) studied this question.

synapsesocial.com/papers/698434a6f1d9ada3c1fb2fd3https://doi.org/10.1209/0295-5075/adcf49/pdf
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