Global stability of interval recurrent neural networks

The robust global exponential stability of a class of interval recurrent neural networks (RNNs) is studied, and a new robust stability criterion is obtained in the form of linear matrix inequality. The problem of robust stability of interval RNNs is transformed into a problem of solving a class of linear matrix inequalities. Thus, the robust stability of interval RNNs can be analyzed by directly using the linear matrix inequalities (LMI) toolbox of MATLAB. Numerical example is given to show the effectiveness of the obtained results.