期刊
NEURAL PROCESSING LETTERS
卷 46, 期 2, 页码 719-745出版社
SPRINGER
DOI: 10.1007/s11063-017-9620-8
关键词
Time scales; Neutral-type competitive neural networks; Pseudo-almost periodic solution; Global exponential stability; Leakage delays
A competitive neural network model was proposed to describe the dynamics of cortical maps in which, there exist two memories: long-term and short-term. In this paper, we investigate the existence and the exponential stability of the pseudo-almost periodic solution of a system of equations modeling the dynamics of neutral-type competitive neural networks with mixed delays in the time-space scales for the first time. The mixed delays include time-varying delays and continuously distributed ones. Based on contraction principle and the theory of calculus on time-space scales, some new criteria proving the convergence of all solutions of the networks toward the unique pseudo-almost periodic solution are derived by using the ad-hoc Lyapunov-Krasovskii functional. Finally, numerical example with graphical illustration is given to confirm our main results.
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