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

Authors :
Chen, Chuan
Li, Lixiang
Peng, Haipeng
Yang, Yixian
Mi, Ling
Wang, Lianhai
Source :
Neurocomputing. Jul2019, Vol. 349, p290-300. 11p.
Publication Year :
2019

Abstract

In this paper, we propose a new fixed-time stability theorem. Numerical simulations show that our upper bound estimate for the settling time is much smaller than those in the existing fixed-time stability theorems. Based on the new fixed-time stability theorem, we investigate the fixed-time synchronization of memristive neural networks (MNNs) by adopting a delay-dependent feedback controller. Numerical simulations are provided to demonstrate the correctness of our theoretical results and the superiority of the new fixed-time stability theorem. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
349
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
136389647
Full Text :
https://doi.org/10.1016/j.neucom.2019.03.040