Impulsive delayed integro-differential inequality and its application on IMNNs with discrete and distributed delays

Impulsive differential inequality is crucial for nonlinear impulsive differential system. In this paper, an impulsive delayed integro-differential inequality is firstly presented and studied. New impulsive inequality is given by M-matrix, proof by contradiction and recursive inequality. Then, the discrete-distributed delayed memristive neural network model is constructed and its exponential stability criteria are obtained by the novel impulsive delayed inequality. Finally, two numerical examples are given to illustrate the effectiveness of exponential stability criteria.