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