Complete synchronization of discrete‐time fractional‐order Cohen–Grossberg neural networks with time delays via adaptive nonlinear controller
Tong Li, Hongli Li, Xiaolin Fan, Long Zhang · Mathematical Methods in the Applied Sciences · 2024
In this paper, we dedicate to investigate complete synchronization of discrete‐time fractional‐order Cohen–Grossberg neural networks (DFCGNNs) with time delays. In order to resolve the problem, we have made the following efforts. First, we establish a fractional‐order convergence principle by employing nabla Laplace transform and analysis techniques. Next, an adaptive nonlinear controller is designed, and then several complete synchronization criteria of DFCGNNs are obtained with the help of inequality techniques and convergence principle we newly establish. Finally, a numerical example is presented to show the validity of theorical results we derive.