Delay-dependent stability criteria of uncertain Markovian jump neural networks with discrete interval and distributed time-varying delays

ALI M. S., Arik S., SARAVANAKURNAR R.

NEUROCOMPUTING, cilt.158, ss.167-173, 2015 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 158
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1016/j.neucom.2015.01.056
  • Dergi Adı: NEUROCOMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.167-173
  • Anahtar Kelimeler: Distributed time-varying delay, Interval time-varying delay, Linear matrix inequality (LMI), Markovian jumping parameters, Neural networks, ROBUST STABILITY, STOCHASTIC STABILITY, STATE ESTIMATION, SYSTEMS
  • İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet

Özet

In this paper, a class of uncertain neural networks with discrete interval and distributed time-varying delays and Markovian jumping parameters (MJPs) are carried out. The Markovian jumping parameters are modeled as a continuous-time, finite-state Markov chain. By using the Lyapunov-Krasovskii functionals (LKFs) and linear matrix inequality technique, some new delay-dependent criteria is derived to guarantee the mean-square asymptotic stability of the equilibrium point. Numerical simulations are given to demonstrate the effectiveness of the proposed method. The results are also compared with the existing results to show the less conservativeness. (C) 2015 Elsevier B.V. All rights reserved.