Global asymptotic stability of Discrete-Time Cellular Neural Networks

Arik S., Kilinc A., Savaci F.

5th IEEE International Workshop on Cellular Neural Networks and Their Applications, London, Kanada, 14 - 17 Nisan 1998, ss.52-55, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/cnna.1998.685329
  • Basıldığı Şehir: London
  • Basıldığı Ülke: Kanada
  • Sayfa Sayıları: ss.52-55
  • İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet

Özet

This paper presents two sufficient conditions for global stability of Discrete-Time Cellular Neural Networks (DTCNNs). It is shown that if the first or second norm of the feedback matrix is smaller than one, then a DTCNN converges to a unique and globally asymptotically stable equilibrium point for every external input.