IEEE Access (Jan 2024)
Synchronized Control of Chaotic Neural Networks With Actuator Saturation
Abstract
This paper investigates the chaotic synchronization of neural networks via sampled-data control with actuator saturation. First, a new generalized looped-functional is constructed by considering valid information from $t_{k}$ to t and from t to $t_{k+1}$ . Then, local stability conditions for the synchronization error system are given based on the Lyapunov stability theory. A sampled-data controller is designed to achieve the synchronization of the driving neural network and the response neural network by solving the convex optimization problem with given conditions. The proposed method’s effectiveness and practicality are numerically verified.
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