Anti-periodic solutions for state-dependent impulsive recurrent neural networks with time-varying and continuously distributed delays


Sayli M., Yilmaz E.

ANNALS OF OPERATIONS RESEARCH, cilt.258, sa.1, ss.159-185, 2017 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 258 Konu: 1
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1007/s10479-016-2192-6
  • Dergi Adı: ANNALS OF OPERATIONS RESEARCH
  • Sayfa Sayıları: ss.159-185

Özet

In this paper, we address a new model of neural networks related to the impulsive phenomena which is called state-dependent impulsive recurrent neural networks with time-varying and continuously distributed delays. We investigate sufficient conditions on the existence and uniqueness of exponentially stable anti-periodic solution for these neural networks by employing method of coincide degree theory and an appropriate Lyapunov function. Moreover, we present an illustrative example to show the effectiveness and feasibility of the obtained theoretical results.