New results on exponential attractivity of multiple almost periodic solutions of cellular neural networks with time-varying delays

We present new results on multi-almost periodicity and attractivity of delayed cellular neural networks (DCNNs). Some criteria are derived for ensuring locally or globally exponential attractivity of multiple almost periodic solutions in designated regions. It is shown that NN-dimensional DCNNs can have a coexistence of 2N2N locally attractive almost periodic solutions. Furthermore, the obtained conclusions have a wider applicable range, improve and complement the existing ones. Finally, computer simulations are given to show the effectiveness of the theoretical results.