TITLE:
Some Further Results on Fixed-Time Synchronization of Neural Networks with Stochastic Perturbations
AUTHORS:
Aminamuhan Abudireman, Mairemunisa Abudusaimaiti, Wanjuan Sun, Jiangyuan Zhao, Yuanshuang Zhang, Abdujelil Abdurahman
KEYWORDS:
Fixed-Time Stability, Stochastic Perturbation, Synchronization, Neural Network
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.10 No.1,
January
26,
2022
ABSTRACT: In this paper, fixed-time (FXT) synchronization issue of a type of neural networks (NNs) with stochastic perturbations is considered. First, we obtained some novel sufficient criteria to guarantee the FXT synchronization of considered networks via introducing two types of controllers and employing some inequality techniques. Lastly, our theoretical results are verified via giving two numerical examples with their Matlab simulations.