Exponential attractor of κκ-almost periodic sequence solution of discrete-time bidirectional neural networks

In this paper, several criteria are obtained for the existence and exponential attractivity of a unique κκ-almost periodic sequence solution of discrete-time bidirectional neural networks (BNNs). Our results generalize the corresponding results about almost periodic sequence solution in common sense. Finally, computer simulations illustrate the dynamic behavior of discrete-time bidirectional neural networks. It is shown that discretization step κκ affects dynamical characteristics of bidirectional neural networks and our results on κκ-almost periodic sequence solution lead to effective estimates of continuous-time neural networks during real-time computations.