Stability Analysis and Synchronization Control of Fractional-Order Inertial Neural Networks With Time-Varying Delay

This paper mainly investigates the stability analysis and synchronization control of a fractional-order time-varying delay inertial neural network. Firstly, a time-varying delay inertial neural network model is established, which is easy to implement in engineering applications. Secondly, based on the properties of the Caputo fractional derivative and the proposed lemma, the original inertial system is transferred into conventional system through the proper variable substitution, and a synchronous control strategy for the time varying delay inertial network is then established. In addition, the stability conditions of a class of Caputo fractional-order time-delay inertial neural networks are given. Finally, three simulation examples are given to verify the rationality and effectiveness of the method proposed in this paper.

Automated summary

This paper investigates the stability analysis and synchronization control of a fractional-order time-varying delay inertial neural network. A time-varying delay inertial neural network model is established for engineering applications. Based on the properties of the Caputo fractional derivative and the proposed lemma, the original inertial system is transformed into a conventional system and a synchronous control strategy is established. The stability conditions of a class of Caputo fractional-order time-delay inertial neural networks are provided. Simulation examples are given to verify the proposed method.