A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks.

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ID: 83736
2020
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Ranked #19 of 55 articles by views in neural networks : the official journal of the international neural network society

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Abstract
In this paper, we derive a new fixed-time stability theorem based on definite integral, variable substitution and some inequality techniques. The fixed-time stability criterion and the upper bound estimate formula for the settling time are different from those in the existing fixed-time stability theorems. Based on the new fixed-time stability theorem, the fixed-time synchronization of neural networks is investigated by designing feedback controller, and sufficient conditions are derived to guarantee the fixed-time synchronization of neural networks. To show the usability and superiority of the obtained theoretical results, we propose a secure communication scheme based on the fixed-time synchronization of neural networks. Numerical simulations illustrate that the new upper bound estimate formula for the settling time is much tighter than those in the existing fixed-time stability theorems. Moreover, the plaintext signals can be recovered according to the new fixed-time stability theorem, while the plaintext signals cannot be recovered according to the existing fixed-time stability theorems.
Reference Key
chen2020aneural Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Chen, Chuan;Li, Lixiang;Peng, Haipeng;Yang, Yixian;Mi, Ling;Zhao, Hui;
Journal neural networks : the official journal of the international neural network society
Year 2020
DOI
S0893-6080(19)30430-7
URL
Keywords
neural networks fixed-time synchronization fixed-time stability

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