| Abstract: |
| This paper investigates the problem of finite-time synchronization in complex-valued fractional-order memristive neural networks (CVMFONNs) with time-varying delays. The focus is on developing novel synchronization criteria and control strategies that ensure finite-time synchronization despite the inherent complexities introduced by fractional-order dynamics, memristive characteristics, and complex-valued states. By employing Lyapunov functional methods and fractional-order calculus, we derive sufficient conditions for finite-time synchronization, accounting for the influence of time-varying delays on system stability. The proposed control schemes are validated through rigorous theoretical analysis and numerical simulations, demonstrating their effectiveness and robustness. Our results contribute to the understanding and application of fractional-order neural networks in real-world scenarios where rapid synchronization is critical, offering potential insights for advancements in neuromorphic computing and complex system modeling. |
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