Chaouki Aouiti, El Abed Assali
In this paper, we study the problem of predefined-time synchronization for distinct-order fractional delayed Cohen-Grossberg neural networks. Fractional-order models are known for their ability to capture memory effects and complex dynamics more accurately than classical integer-order systems. In particular, allowing distinct-order in the drive and response systems provides additional flexibility in modeling. To achieve synchronization, we propose two control strategies that provide sufficient conditions for predefined-time synchronization of the addressed model. These strategies are based on the construction of an appropriate Lyapunov function and the use of fractional calculus properties. Finally, two numerical examples are provided to verify the effectiveness of the proposed methods.