Global asymptotic stability analysis of bidirectional associative memory neural networks with time delays

Arik S.

IEEE TRANSACTIONS ON NEURAL NETWORKS, cilt.16, sa.3, ss.580-586, 2005 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 3
  • Basım Tarihi: 2005
  • Doi Numarası: 10.1109/tnn.2005.844910
  • Dergi Adı: IEEE TRANSACTIONS ON NEURAL NETWORKS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.580-586
  • İstanbul Üniversitesi Adresli: Evet

Özet

This paper presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with distributed time delays. The results impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all continuous nonmonotonic neuron activation functions. It is shown that in some special cases of the results, the stability criteria can be easily checked. Some examples are also given to compare the results with the previous results derived in the literature.