Novel Results on Fixed-Time Complex Projective Lag Synchronization for Fuzzy Complex-Valued Neural Networks With Inertial Item

This paper focuses on investigating fuzzy complex-valued neural networks with inertial item. By utilizing fixed-time stability theory and inequality techniques, we designed two types of feedback controllers and obtained some new criteria to ensure that the system achieves fixed-time complex projective lag synchronization(CPLS). Compared with previous works, we study the complex-value system as a whole, and compared to ordinary synchronization, CPLS has a broader range of applications. Finally, we provide numerical simulations to verify the effectiveness of the theoretical results.