Further Analysis on Preassigned-time Anti-synchronization of Memristive Inertial BAM Neural Networks

This paper studies the preassigned time anti-synchronization control problem of a class of bidirectional associative memory (BAM) neural networks with inertia terms and memristor characteristics. By constructing a novel Lyapunov-Krasovskii function and combining it with the latest fixed-time stability theory, it strictly proves the sufficient conditions for the system to achieve anti-synchronization within the preassigned time. Numerical simulations further verified the effectiveness and superiority of the method, especially demonstrating higher accuracy and flexibility when dealing with high-order dynamics and memristor-based systems.