Skip to main navigation Skip to search Skip to main content

The stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control

  • Weiping Wang
  • , Xin Yu
  • , Xiong Luo
  • , Long Wang
  • , Lixiang Li
  • , Jurgen Kurths
  • , Wenbing Zhao
  • , Jiuhong Xiao
  • University of Science and Technology Beijing
  • Humboldt-University
  • Beijing University of Posts and Telecommunications
  • Potsdam Institute for Climate Impact Research
  • Cleveland State University

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we propose a new model of memristive multidirectional associative memory neural networks, which concludes the time-varying delays in leakage terms via sampleddata control. We use the input delay method to turn the sampling system into a continuous time-delaying system. Then we analyze the exponential stability and asymptotic stability of the equilibrium points for this model. By constructing a suitable Lyapunov function, using the Lyapunov stability theorem and some inequality techniques, some sufficient criteria for ensuring the stability of equilibrium points are obtained. Finally, numerical examples are given to demonstrate the effectiveness of our results.
Original languageEnglish
Article numbere0204002
JournalPLoS ONE
Volume13
Issue number9
DOIs
StatePublished - Sep 1 2018

Cite this