Global Polynomial Synchronization of Uncertain Complex-Valued Reaction--Diffusion T--S Fuzzy Memristive Neural Networks With Proportional Delays Under Adaptive Event-Triggered Control
Abstract
This article addresses global polynomial synchronization (GPS) for uncertain complex-valued reaction-diffusion Takagi-Sugeno (T-S) fuzzy memristive neural networks (MNNs) with proportional delays. First, the interval matrix theory is extended, for the first time, to achieve the characterization of complex-domain memristors. Second, novel Lyapunov functionals are constructed by exploiting conjugate transpose properties, circumventing the decomposition of complex states into real and imaginary parts. Subsequently, two event-triggered controllers are designed to derive synchronization criteria, further considering the case where GPS degenerates into global asymptotic synchronization (GAS). Finally, the validity of the theoretical results is verified through two numerical examples.
Fields of Study & Subjects
Neural Networks Stability and Synchronization
Advanced Memory and Neural Computing
Distributed Control Multi-Agent Systems
Publication details
- Journal / source
- IEEE Transactions on Neural Networks and Learning Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 37
- Issue
- 9
- Pages
- 4369–4380
- Publication date
- 6 March 2026
- Language
- EN