New robust stability results for bidirectional associative memory neural networks with multiple time delays
Yükleniyor...
Dosyalar
Tarih
2012-08-01
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, the robust stability problem is investigated for a class of bidirectional associative memory (BAM) neural networks with multiple time delays. By employing suitable Lyapunov functionals and using the upper bound norm for the interconnection matrices of the neural network system, some novel sufficient conditions ensuring the existence, uniqueness and global robust stability of the equilibrium point are derived. The obtained results impose constraint conditions on the system parameters of neural network independent of the delay parameters. Some numerical examples and simulation results are given to demonstrate the applicability and effectiveness of our results, and to compare the results with previous robust stability results derived in the literature.
Açıklama
Anahtar Kelimeler
Equilibrium and stability analysis, Bidirectional associative memory neural networks, Lyapunov functionals, Global asymptotic stability, Reaction-Diffusion terms, Varying delays, Exponential stability, Distributed delays, Neutral-Type, Criterion, Discrete, Passivity
Kaynak
Applied Mathematics and Computation
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
218
Sayı
23
Künye
Senan, S., Arik, S. & Liu, D. (2012). New robust stability results for bidirectional associative memory neural networks with multiple time delays. Applied Mathematics and Computation, 218(23), 11472-11482. doi:10.1016/j.amc.2012.04.075
