New results for global stability of Cohen-Grossberg neural networks with discrete time delays


Orman Z. , Arik S.

NEURAL INFORMATION PROCESSING, PT 1, PROCEEDINGS, cilt.4232, ss.570-579, 2006 (SCI İndekslerine Giren Dergi) identifier

  • Cilt numarası: 4232
  • Basım Tarihi: 2006
  • Dergi Adı: NEURAL INFORMATION PROCESSING, PT 1, PROCEEDINGS
  • Sayfa Sayıları: ss.570-579

Özet

This paper studies the global convergence properties of Cohen-Grossberg neural networks with discrete time delays. Without assuming the symmetry of interconnection weight coefficients, and the monotonicity and differentiability of activation functions, and by employing Lyapunov functionals, we derive new delay independent sufficient conditions under which a delayed Cohen-Grossberg neural network converges to a globally asymptotically stable equilibrium point. Some examples are given to illustrate the advantages of the results over the previously reported results in the literature.