Neural Processing Letters

, Volume 26, Issue 3, pp 191–200

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

Authors

    • School of Mathematics and Computing SciencesChangsha University of Science and Technology
  • Haomin Zhang
    • School of MathematicsCentral South University
  • Yong Wang
    • Department of MathematicsHarbin Institute of Technology
  • Jiezhong Zou
    • School of MathematicsCentral South University
  • Zheng Yu
    • School of MathematicsCentral South University
  • Zhenting Hou
    • School of MathematicsCentral South University
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

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