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International Journal of Nonlinear Sciences and Numerical Simulation

Editor-in-Chief: Birnir, Björn

Editorial Board Member: Armbruster, Dieter / Bessaih, Hakima / Chou, Tom / Grauer, Rainer / Marzocchella, Antonio / Rangarajan, Govindan / Trivisa, Konstantina / Weikard, Rudi

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2191-0294
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Volume 18, Issue 1 (Feb 2017)

Issues

Almost Periodic Solution in a Lotka–Volterra Recurrent Neural Networks with Time-Varying Delays

Li Yang
  • Li Yang, School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Zhouhong Li / Liyan Pang
  • Liyan Pang, School of Mathematics and Computer Science, Ningxia Normal University, Guyuan, Ningxia 756000, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Tianwei Zhang
  • Corresponding author
  • Tianwei Zhang, City College, Kunming University of Science and Technology, Kunming 650051, China
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Published Online: 2016-12-17 | DOI: https://doi.org/10.1515/ijnsns-2015-0171

Abstract:

By means of Mawhin’s continuation theorem of coincidence degree theory and Lyapunov function, some simple sufficient conditions are obtained for the existence and stability of a unique positive almost periodic solution of a delayed Lotka–Volterra recurrent neural networks. To a certain extent, the work in this paper corrects the defect of a recent paper. Finally, an example and simulations are given to illustrate the feasibility and effectiveness of the main result.

Keywords: almost periodicity; Lotka–Volterra; neural networks; coincidence degree

MSC 2010: 34K14; 92B20; 92D25

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About the article

Received: 2015-11-16

Accepted: 2016-11-27

Published Online: 2016-12-17

Published in Print: 2017-02-01


This work was supported by Tian Yuan Fund of NSFC (No.11526180), Yunnan University of Finance and Economics Scientific Research Found Project (No.YC2015D09), Yunnan Province Education Department Scientific Research Fund Project (No.2015Y275), Natural Science Foundation of Yunnan Province of China under Grant No. 2014FD049 and Natural Science Foundation of Ningxia Province under Grant No. NZ15255.


Citation Information: International Journal of Nonlinear Sciences and Numerical Simulation, ISSN (Online) 2191-0294, ISSN (Print) 1565-1339, DOI: https://doi.org/10.1515/ijnsns-2015-0171.

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