Almost Periodic Solution for a Lotka-Volterra Recurrent Neural Networks with Harvesting Terms on Time Scales

By using the theory of exponential dichotomy and Banach fixed point theorem, this paper is concerned with the problem of the existence and uniqueness of almost periodic solution in a harvesting Lotka-Volterra recurrent neural networks on time scales. To a certain extent, our work in this paper corrects the defect in [Y.G. Liu, B.B. Liu, S.H. Ling, The almost periodic solution of Lotka-Volterra recurrent neural networks with delays, Neurocomputing 74 (2011) 1062-1068]. Further, by constructing a suitable Lyapunov function, some simple sufficient conditions are obtained for the local asymptotical stability of the above model. Finally, an example is given to illustrate the feasibility and effectiveness of the main result.