The almost periodic solution of lotka-volterra recurrent neural networks with delays

Elsevier BV
Publication Type:
Journal Article
Neurocomputing, 2011, 74 (6), pp. 1062 - 1068
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By the fixed-point theorem subject to different polyhedrons and some inequalities (e.g.,the inequality resulted from quadratic programming), we obtain three theorems for the LotkaâVolterra recurrent neural network shaving almost periodic coefficients and delays. One of the three theorems can only ensure the existence of an almost periodic solution, whose existence and uniqueness the other two theorems are about. By using Lyapunov function, the sufficient condition guaranteeing the global stability of the solution is presented. Furthermore, two numerical examples are employed to illustrate the feasibility and validity of the obtained criteria. Compared with known results, the networks model is novel, and the results are extended and improved.
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