DOIONLINE

DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-11729

Publish In
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN
Journal Home
Volume Issue
Issue
Volume-6, Issue-4  ( Apr, 2018 )
Paper Title
Global Asymptotic Robust Stability of Dynamical Neural Networks with Constant Time Delays
Author Name
Sabri Arik
Affilition
Department of Computer Engineering, Faculty of Engineering, Istanbul University 34320 Avcilar, Istanbul, Turkey
Pages
1-5
Abstract
This paper deals with the problem of global asymptotic robust stability of continuous-time neural networks with constant time delays. By employing the Lyapunov stability theorems and using some basic properties of the interval matrices, we derive a new delay independent sufficient condition for the uniqueness and global robust asymptotic stability of the equilibrium point for delayed neural networks. The obtained result can be easily verified and it is only dependent on the network parameters of neural system. Keywords- Robust Stability Analysis, Neural Networks, Lyapunov Stability Theorems.
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