In this paper, a general class of memristive neural networks with variable delays is studied. By utilizing control theory and nonsmoooth analysis, two sufficient criteria ensuring input-to-state stability of memristive neural networks with variable delays are firstly obtained which are novel and more practical than the previous works in the literature. Finally, a numerical example is given to demonstrate the effectiveness of our results.
['Kai Zhong', 'Qiqi Yang', 'Song Zhu']
New algebraic conditions for ISS of memristive neural networks with variable delays