An Analysis of Global Stability of Takagi-Sugeno Fuzzy Cohen-Grossberg Neural Networks with Time Delays

Senan S.

NEURAL PROCESSING LETTERS, cilt.48, sa.3, ss.1693-1704, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 48 Sayı: 3
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1007/s11063-018-9792-x
  • Dergi Adı: NEURAL PROCESSING LETTERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1693-1704
  • İstanbul Üniversitesi Adresli: Evet

Özet

This paper deals with the problem of the global asymptotic stability of Takagi-Sugeno (T-S) fuzzy Cohen-Grossberg neural networks with multiple time delays. By using Lyapunov method and some basic properties of matrices, and employing the nondecreasing and slope-bounded activation functions, an easily verifiable sufficient criterion is derived to establish the asymptotic stability of a general class of (T-S) fuzzy Cohen-Grossberg neural networks with multiple time delays. The obtained stability condition establishes some relationships between the network parameters of the neural network model independently of the delay parameters. A numerical example is also given to illustrate the effectiveness of the theoretical results.