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  Journal Paper

Paper Title
Global Asymptotic Robust Stability of Dynamical Neural Networks with Constant Time Delays

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.


Author - Sabri Arik

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| Published on 2018-06-09
   
   
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