Work

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

Year: 2022

Type: article

Abstract: 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.

Source: IEEE Access

DOI: 10.1109/access.2022.3178123

Authors: Yihong Liu, Yeguo Sun, Lei Liu

Institution: Huainan Normal University

Language: English

Topic: Neural Networks Stability and Synchronization

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,850

Funders: National Natural Science Foundation of China, Natural Science Foundation of Anhui Province