Further Analysis on Fixed/Preassigned-Time Projective Synchronization of Discontinuous Fuzzy Delayed Inertial Neural Networks
Our goal is addressing the problems of preassigned-time projective synchronization and fixed-time projective synchronization of the system that studied in our article, and fuzzy terms, mixed delays, inertial terms and discontinuous activation function are also included in this system. Further, the results of this article are based on the latest fixed-time stabilization lemma. Through the construction of adaptative Lyapunov function and new corresponding feedback controllers, we arrive at the results of fixed-time projective synchronization and preassigned-time projective synchronization about investigated neural networks, and we are using a non-reduced-order approach. The proposed results are more extensive in comparison with traditional anti-synchronization and synchronization. At the end of our article, to demonstrate the advantage of our outcomes, we display some simulation example.
Authors
- 李岩 Li Yan (ORCID: https://orcid.org/0000-0002-7978-1801)
- Guodong Zhang (ORCID: https://orcid.org/0000-0002-8323-9126)
- Xiao Zhou
- Jing Han (ORCID: https://orcid.org/0000-0002-6463-8041)
Institutions
- Minzu University of China (CN)
- Huazhong Agricultural University (CN)
- Wuhan Business University (CN)
Publication Details
- Journal
- IEEE Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/access.2025.3582344
- Citations
- 2
- Primary Topic
- Neural Networks Stability and Synchronization
- Type
- article
- Field-Weighted Citation Impact
- 2.97
Funders
- National Natural Science Foundation of China