Global Polynomial Synchronization of Uncertain Complex-Valued Reaction–Diffusion T–S Fuzzy Memristive Neural Networks With Proportional Delays Under Adaptive Event-Triggered Control

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.