Global asymptotic stability of a class of neural networks with time varying delays

Ensari T., Arik S., Tavsanoglu V.

IEEE International Symposium on Circuits and Systems, Vancouver, Kanada, 23 - 26 Mayıs 2004, ss.820-823 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Basıldığı Şehir: Vancouver
  • Basıldığı Ülke: Kanada
  • Sayfa Sayıları: ss.820-823
  • İstanbul Üniversitesi Adresli: Evet

Özet

This paper presents a new sufficient condition for the uniqueness and global asymptotic stability (GAS) of the equilibrium point for a larger class of neural networks with time varying delays. It is shown that the use of a more general type of Lyapunov-Krasovskii functional leads to establish global asymptotic stability of a larger class of delayed neural networks than the neural network model considered in some previous papers.