Synchronization of Time-Varying Delayed Neural Networks by Fixed-Time Control | Zendy

Yuhua Xu | Zendy; Xiaoqun Wu | Zendy; Chao Xu | Zendy

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Synchronization of Time-Varying Delayed Neural Networks by Fixed-Time Control

Author(s) -

Yuhua Xu,

Xiaoqun Wu,

Chao Xu

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2883417

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This paper discusses synchronization of time-varying delayed neural networks by fixed-time control. First, several new fixed-time stability theorems of the dynamic system are discussed, and the estimation of the convergence time is also gained. Compared with some existing results, the convergence time given in this paper can be less conservative and more accurate. Second, as one of the important applications of fixed-time stability, several novel sufficient criteria are derived such that the two time-varying neural networks can be synchronized within a fixed-time. Finally, the simulation result is presented to show the effectiveness of the theoretical result.

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