Work

Global exponential H ∞ synchronization of multi-weighted coupled neural networks with multiple time-varying delays

Year: 2025

Type: article

Abstract: This paper investigates the global exponential H ∞ synchronization problem for multi-weighted coupled neural networks (MWCNNs) with multiple time-varying delays. A bounded real lemma (BRL) is firstly established based on the solutions of delayed MWCNNs, which can be used to derive that delayed MWCNNs reach global exponential H ∞ synchronization. On the basis of the proposed BRL, an aperiodically intermittent controller (AIC) for delayed MWCNNs is proposed to improve synchronization performance. As no Lyapunov–Krasovskii functional (LKF) is constructed in the proposed method, the computational complexity is significantly reduced. Finally, the theoretical result is verified through a numerical example, and applied to encryption and decryption of color images.

Source: Systems & Control Letters

DOI: 10.1016/j.sysconle.2025.106282

Authors: Zhuo Ren, Yu Xue, Tingting Yu

Institution: Heilongjiang University

Language: English

Topic: Neural Networks Stability and Synchronization

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,910

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