Global exponential stability of periodic solution of neural network with variable coefficients and time-varying delays

By using the continuation theorem of Mawhin’s coincidence degree theory and some inequality techniques, some new sufficient conditions are obtained ensuring existence and global exponential stability of periodic solution of neural networks with variable coefficients and time-varying delays. These results are helpful to design globally exponentially stable and oscillatory neural networks. Finally, the validity and performance of the obtained results are illustrated by two examples.