Neural Processing Letters

, Volume 26, Issue 3, pp 191–200

pth Moment Exponential Stability of Stochastic Cohen-Grossberg Neural Networks With Time-varying Delays

  • Enwen Zhu
  • Haomin Zhang
  • Yong Wang
  • Jiezhong Zou
  • Zheng Yu
  • Zhenting Hou
Article

DOI: 10.1007/s11063-007-9051-z

Cite this article as:
Zhu, E., Zhang, H., Wang, Y. et al. Neural Process Lett (2007) 26: 191. doi:10.1007/s11063-007-9051-z
  • 81 Views

Abstract

The pth moment exponential stability of stochastic Cohen-Grossberg with time-varying delays is investigated in this paper. A set of novel sufficient conditions on pth moment exponential stability are given for the considered system by using the well-known Razumikhin-type theorem. Finally, two examples with their numerical simulations are provided to show the correctness of our analysis.

Keywords

Stochastic Cohen-Grossberg neural networkspth moment exponential stabilityRazumikhin-type theorem

Mathematics Subject Classifications (2000)

92B2093E1534K50

Copyright information

© Springer Science+Business Media, LLC. 2007

Authors and Affiliations

  • Enwen Zhu
    • 1
  • Haomin Zhang
    • 2
  • Yong Wang
    • 3
  • Jiezhong Zou
    • 2
  • Zheng Yu
    • 2
  • Zhenting Hou
    • 2
  1. 1.School of Mathematics and Computing SciencesChangsha University of Science and TechnologyChangsha, HunanP. R. China
  2. 2.School of MathematicsCentral South UniversityChangsha, HunanP. R. China
  3. 3.Department of MathematicsHarbin Institute of TechnologyHarbinP. R. China