Convergence of Discrete-Time Neural Networks with Delays ∗
Lin Wang, Xingfu Zou · 2008
An LMI (Linear Matrix Inequality) approach and an embedding tech- nique are employed to derive some sufficient conditions for the global exponential stability of discrete-time neural networks with time-dependent delays and constant parameters. For networks with time-dependent parameters but constant delays, by using the property of internally chain transitive sets, it is shown that these conditions are also sufficient for the convergence of the networks. AMS Subject Classifications: 92B20, 39A11