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Mathematics 2019, 7(4), 321; https://doi.org/10.3390/math7040321

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

1
School of Mathematics and Computer Science, Yunnan Minzu University, Kunming 650500, Yunnan, China
2
Department of Mathematics, Yunnan University, Kunming 650091, Yunnan, China
*
Author to whom correspondence should be addressed.
Received: 26 February 2019 / Revised: 23 March 2019 / Accepted: 25 March 2019 / Published: 29 March 2019
(This article belongs to the Section Network Science)
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PDF [506 KB, uploaded 29 March 2019]
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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. View Full-Text
Keywords: competitive neural networks; leakage delays; almost periodic solutions; time scales competitive neural networks; leakage delays; almost periodic solutions; time scales
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Li, B.; Li, Y.; Meng, X. The Existence and Global Exponential Stability of Almost Periodic Solutions for Neutral-Type CNNs on Time Scales. Mathematics 2019, 7, 321.

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