A sufficient condition for absolute stability of a larger class of dynamical neural networks

Arik, SABRİ; Tavsanoglu, V

doi:10.1109/81.847881

A sufficient condition for absolute stability of a larger class of dynamical neural networks

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, cilt.47, sa.5, ss.758-760, 2000 (SCI-Expanded, Scopus)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 47 Sayı: 5
Basım Tarihi: 2000
Doi Numarası: 10.1109/81.847881
Dergi Adı: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Sayfa Sayıları: ss.758-760
Anahtar Kelimeler: absolute stability, neural networks
İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet

Özet

In this paper, we present a sufficient condition for absolute stability of a larger class of dynamical neural networks. It is shown that the H-matrix condition on the interconnection matrix ensures the existence, uniqueness and global asymptotic stability (GAS) of the equilibrium point with respect to slope-limited activation functions.