Robust stability analysis of a class of hopfield neural networks with multiple delays

  • Authors:

  • Huaguang Zhang;Ce Ji;Derong Liu

  • Affiliations:

  • Institute of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China;Institute of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China;Department of Electrical and Computer, University of Illinois, Chicago, IL

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
  • Year:
  • 2005

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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.