Exponential stability of discrete-time recurrent neural networks with time-varying delays in the leakage terms and linear fractional uncertainties
Mengxian Hu, J. Cao, Anqi Hu · IMA Journal of Mathematical Control and Information · 2013
A class of discrete-time recurrent neural networks model is presented with the introduction of time-varying delays in the leakage terms and linear fractional uncertainties in parameters. The exponential stability analysis problem is studied, for the first time, for such kind of neural networks. In terms of linear matrix inequality approach, some delay-dependent stability criteria are established for the considered neural networks via a Lyapunov–Karasovskii functional. Three numerical examples are given to show the effectiveness of the theoretical results.