Improved exponential stability criteria for discrete-time neural networks with time-varying delay ?
The problem of robust exponential stability for a class of discrete-time recurrent neural networks with time-varying delay is investigated. By constructing a new augmented LyapunovKrasovskii functional, some new delay-dependent stable criteria are obtained. These criteria are formulated in the forms of linear matrix inequality (LMI). Compared with some previous results, the new conditions obtained in this paper are less conservative. Three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed method.
discrete-time neural networks time-varying delays robust exponential stability delay-dependent stability global exponential stability