The existence and exponential attractivity of κ-almost periodic sequence solution of discrete time neural networks

In the present paper, several sufficient conditions are obtained for the existence and exponential attractivity of a unique kappa-almost periodic sequence solution of discrete time neural network. Our results generalize the corresponding results about almost periodic sequence solution in common sense. It is shown that discretization step kappa affects the dynamical characteristics of discrete-time analogues of continuous time neural networks and exponential convergence is dependent on small discretization step size. Our results on exponential attractivity of kappa-almost periodic sequence solution can provide us with relevant estimates on how precise such networks can perform during real-time computations. Finally, computer simulations are performed in the end to show the feasibility of our results.