|Quasi-synchronization of Hybrid Coupled Reaction-diffusion Neural Networks with Parameter Mismatches via Time-space Sampled-data Control
Xingru Li, Xiaona Song*, Zhaoke Ning, and Junwei Lu
International Journal of Control, Automation, and Systems, vol. 19, no. 9, pp.3087-3100, 2021
Abstract : This paper is concerned with the quasi-synchronization problem for a class of hybrid coupled neural networks with reaction diffusion, where the mismatched parameter and time-varying delay are considered in the system model. At first, a time-space sampled-data control is introduced, which not only effectively saves limited network bandwidth compared to traditional control strategies, but also improves the cyber-security of communications. Next, based on the Lyapunov function method and inequality techniques, some sufficient conditions are derived to guarantee the quasi-synchronization of hybrid coupled neural networks with mismatched parameter and reaction-diffusion, and the convergence region of quasi-synchronization is derived using the improved Halanay’s inequality. Finally, the validity and practicability of the derived criteria are verified by three numerical examples and an application example, respectively.
Hybrid coupling, neural networks, parameter mismatch, quasi-synchronization, time-space sampleddata control.