Application of Wide Learning System in Genesio System Synchronization - Đỗ Văn Tân; Bùi Thế Thành; Phạm Đức Hùng; Phạm Ngọc Thắng (Journal of Technical Education Science, 2025)
In this paper, the authors will introduce the application of a deep learning system to synchronize the Genesio chaotic system. The Genesio system is a nonlinear system with high complexity, and to synchronize the system, it is necessary to combine different formulas and algorithms, along with neural networks, to ensure the goal of optimizing inputs, minimizing system errors at the output, and achieving the desired signals. The synchronization scheme uses Lyapunov's theorem to maintain the system's stability, which ensures that the simulation results achieve higher accuracy. A simulation of the synchronized system is carried out using software with an application for synchronizing the Genesio system. The simulation results demonstrate accuracy and faster synchronization capability when compared to other traditional methods. Therefore, this research confirms that the use of a deep learning system combined with neural network techniques and stability theory can provide a powerful and optimal solution for controlling and synchronizing the Genesio system.