Topology Identification of Multilayer Complex Dynamical Networks with Multiple Weights Considering Derivative Coupling
This paper addresses the topology identification problem of multilayer complex dynamical networks with multiple weights, considering derivative coupling. First, we propose a multilayer complex dynamical network model with multiple weights that includes derivative coupling. Using the drive-response method, we construct the response network and derive the error dynamical equation for both the drive and response networks. Next, we design an appropriate controller and topology identifiers for the multilayer complex dynamical networks with multiple weights. By applying Lyapunov stability theory, we ensure the stability of the error system, which enables the topology identification of the drive network and allows us to determine its structure. Finally, the theoretical results of this paper are validated through numerical simulations.
Authors
- Guo‐Ping Jiang (ORCID: https://orcid.org/0000-0001-9448-0989)
- Lu Hao (ORCID: https://orcid.org/0000-0002-4305-7766)
- Yayong Wu (ORCID: https://orcid.org/0000-0001-7969-8832)
- Ying Zheng (ORCID: https://orcid.org/0009-0006-9148-374X)
Institutions
- Nanjing University of Posts and Telecommunications (CN)
Publication Details
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1109/cac63892.2024.10865525
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China