Abstract
This article aims to study fixed-time projective lag synchronization(FXPLS) and preassigned-time projective lag synchronization(PTPLS) of hybrid inertial neural networks(HINNs) with state-switched and discontinuous activation functions(DAFs). By constructing new hybrid fixed-time control and based on theory of non-smooth analysis, we achieve novel results on FXPLS for such HINNs. Through designing novel hybrid preassigned-time control, new criteria on PTPLS of the HINNs is also taken into account. And as distinct from recent works, the FXPLS and PTPLS results are established via non-variable substitution and in a more generalized framework than common synchronization, which also has more extensive practical applications. Finally, example simulations are displayed to set forth the validity of the acquired FXPLS and PTPLS.
| Original language | English |
|---|---|
| Pages (from-to) | 9950-9973 |
| Number of pages | 24 |
| Journal | Journal of the Franklin Institute |
| Volume | 360 |
| Issue number | 13 |
| DOIs | |
| Publication status | Published - Sept 2023 |
Funding
This work is supported by the National Science Foundation of China under Grant No. 61976228 and National Key Research and Development Project of China under Grant 2020YFA0714301.
| Funders | Funder number |
|---|---|
| National Natural Science Foundation of China | 61976228 |
| National Key Research and Development Program of China | 2020YFA0714301 |
Keywords
- Fixed-time projective lag synchronization
- Hybrid inertial neural networks
- Preassigned-time lag projective synchronization
- Time delays
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Computer Networks and Communications
- Applied Mathematics
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