The Existence and Global Exponential Stability of Almost Periodic Solutions for Neutral-Type CNNs on Time Scales

Bing Li, Yongkun Li and Xiaofang Meng
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Bing Li: School of Mathematics and Computer Science, Yunnan Minzu University, Kunming 650500, Yunnan, China
Yongkun Li: Department of Mathematics, Yunnan University, Kunming 650091, Yunnan, China
Xiaofang Meng: Department of Mathematics, Yunnan University, Kunming 650091, Yunnan, China

Mathematics, 2019, vol. 7, issue 4, 1-25

Abstract: In this paper, neutral-type competitive neural networks with mixed time-varying delays and leakage delays on time scales are proposed. Based on the contraction fixed-point theorem, some sufficient conditions that are independent of the backwards graininess function of the time scale are obtained for the existence and global exponential stability of almost periodic solutions of neural networks under consideration. The results obtained are brand new, indicating that the continuous time and discrete-time conditions of the network share the same dynamic behavior. Finally, two examples are given to illustrate the validity of the results obtained.

Keywords: competitive neural networks; leakage delays; almost periodic solutions; time scales (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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