An Analysis of Stability of Multiple Delayed Cohen-Grossberg Neural Networks of Neutral Type


FAYDASIÇOK Ö., ARIK S.

7th International Conference on Mathematics and Computers in Sciences and Industry (MCSI), Athens, Yunanistan, 22 - 24 Ağustos 2022, ss.55-60, (Tam Metin Bildiri) identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/mcsi55933.2022.00016
  • Basıldığı Şehir: Athens
  • Basıldığı Ülke: Yunanistan
  • Sayfa Sayıları: ss.55-60
  • İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet

Özet

This research paper presents new results on global asymptotic stability of a larger class of delayed Cohen-Grossberg neural systems involving multiple time delays and multiple neutral delays including continuous Lipschitz activation functions by utilising a modified novel type Lyapunov functional. The derived robust stability conditions are expressed independently of constant delay terms and propose various new relationships among the constant network elements of this neural system. Therefore, the applicability and validity of these newly proposed robust stability criteria for neural network of this class may be easily checked. The very detailed comparisons among the results of this research article and the existing corresponding literature results are also made by studying a numerical example.