AJAS Cover
Frequency: Continuous
ISSN: 1546-9239 (Print)
ISSN: 1554-3641 (Online)
Research Article Open Access

New sufficient condition of Discrete-time systems of neural networks

Manlika Tanusit1 and Kreangkri Ratchagit1
  • 1 Department of Mathematics and Statistics, Faculty of Science, Maejo University, Chiang Mai 50290, Thailand

Abstract

Problem statement: In this study, we derive a new sufficient condition for asymptotic stability of the zero solution of delay-differential system of neural networks in terms of certain matrix inequalities by using a discrete analog of the new Lyapunov second method. Conclusion/Recommendations: The problem is solved by applying a novel Lyapunov functional and an improved delay-dependent stability criterion is obtained in terms of a linear matrix inequality.

American Journal of Applied Sciences
Volume 8 No. 2, 2011, 113-115

DOI: https://doi.org/10.3844/ajassp.2011.113.115

Submitted On: 3 February 2011 Published On: 28 February 2011

How to Cite: Tanusit, M. & Ratchagit, K. (2011). New sufficient condition of Discrete-time systems of neural networks. American Journal of Applied Sciences, 8(2), 113-115. https://doi.org/10.3844/ajassp.2011.113.115

Open AccessCopyright: © 2011 Manlika Tanusit and Kreangkri Ratchagit. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • 3,404 Views
  • 2,599 Downloads
  • 0 Citations

Download

Keywords

  • Asymptotic stability
  • delay-differential system
  • neural networks
  • lyapunov function
  • matrix inequalities
  • discrete-time systems