Robust Stability Analysis of a Class of Hopfield Neural Networks with Multiple Delays

  • Huaguang Zhang
  • Ce Ji
  • Derong Liu
Conference paper

DOI: 10.1007/11427391_32

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3496)
Cite this paper as:
Zhang H., Ji C., Liu D. (2005) Robust Stability Analysis of a Class of Hopfield Neural Networks with Multiple Delays. In: Wang J., Liao X., Yi Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg

Abstract

The robust stability of a class of Hopfield neural networks with multiple delays is analyzed. Sufficient conditions for the global robust stability of the equilibrium point are established through constructing a suitable Lyapunov-Krasovskii functional. The present results take the form of linear matrix inequalities, and are computationally efficient. In addition, the results are independent of delays and established without assuming differentiability and monotonicity of the activation function.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Huaguang Zhang
    • 1
  • Ce Ji
    • 1
  • Derong Liu
    • 2
  1. 1.Institute of Information Science and EngineeringNortheastern UniversityShenyangChina
  2. 2.Department of Electrical and ComputerUniversity of IllinoisChicagoUSA

Personalised recommendations