Robust stability of Cohen-Grossberg neural networks via state transmission matrix

IEEE Trans Neural Netw. 2009 Jan;20(1):169-74. doi: 10.1109/TNN.2008.2009119.

Abstract

This brief is concerned with the global robust exponential stability of a class of interval Cohen-Grossberg neural networks with both multiple time-varying delays and continuously distributed delays. Some new sufficient robust stability conditions are established in the form of state transmission matrix, which are different from the existing ones. Furthermore, a sufficient condition is also established to guarantee the global stability for this class of Cohen-Grossberg neural networks without uncertainties. Three examples are used to show the effectiveness of the obtained results.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Neural Networks, Computer*
  • Time Factors