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Giebel, S. and Rainer, M. (2011) Stochastic Processes Adapted By Neural Networks with Application to Climate, Energy, and Finance. Applied Mathematics and Computation, 218, 1003-1007.
https://doi.org/10.1016/j.amc.2011.03.121

has been cited by the following article:

• 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.