Synchronization in fractional discrete neural networks: constant and variable orders cases

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The objective of this study is to explore synchronizationa spects of discrete fractional neural networks, encompassing both constant and variable orders. By employing nonlinear feedback control techniques, we establish a sufficient criterion to ensure the synchronization of discrete fractional neural networks with constant orders. Moreover, under certain specified circumstances, we employ the Lyapunov functional to analyze the synchronization of discrete fractional neural networks with variable orders. This synchronization condition is entirely reliant on system parameters, facilitating straightforward verification and implementation. To assess the efficacy and practicality of the proposed methodologies, we present two illustrative numerical examples. These examples vividly demonstrate the successful synchronization of discrete fractional neural networks.