ALMOST PERIODIC SYNCHRONIZATION FOR COMPLEX-VALUED NEURAL NETWORKS WITH TIME-VARYING DELAYS AND IMPULSIVE EFFECTS ON TIME SCALES

Lihua Dai; Zhouhong Li

doi:10.11948/20220214

2023 Volume 13 Issue 2

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Lihua Dai, Zhouhong Li. ALMOST PERIODIC SYNCHRONIZATION FOR COMPLEX-VALUED NEURAL NETWORKS WITH TIME-VARYING DELAYS AND IMPULSIVE EFFECTS ON TIME SCALES[J]. Journal of Applied Analysis & Computation, 2023, 13(2): 893-912. doi: 10.11948/20220214

Citation:

Lihua Dai, Zhouhong Li. ALMOST PERIODIC SYNCHRONIZATION FOR COMPLEX-VALUED NEURAL NETWORKS WITH TIME-VARYING DELAYS AND IMPULSIVE EFFECTS ON TIME SCALES[J]. Journal of Applied Analysis & Computation, 2023, 13(2): 893-912. doi: 10.11948/20220214

ALMOST PERIODIC SYNCHRONIZATION FOR COMPLEX-VALUED NEURAL NETWORKS WITH TIME-VARYING DELAYS AND IMPULSIVE EFFECTS ON TIME SCALES

Lihua Dai^1,2,
Zhouhong Li^3,4, ,

1.
School of Mathematics and Statistics, Southwest University, 400715 Chongqing, China
2.
School of Mathematics and Statistics, Puer University, 665000 Puer, Yunnan, China
3.
School of Statistics and Mathematics, Yunnan University of Finance and Economics, 650221 Kunming, Yunnan, China
4.
Department of Mathematics, Yuxi Normal University, 653100 Yuxi, Yunnan, China

Corresponding author: Email address: zhouhli@yeah.net(Z. Li)
Fund Project: The authors were supported by the Science Research Fund of Education Department of Yunnan Province of China(2022J0986, 2022Y489), and Youth academic and technical leader of Pu'er College (QNRC21-01)

Abstract

Abstract

We propose a class of complex-valued neural networks with time-varying delays and impulsive effects on time scales. By employing the Banach fixed point theorem and differential inequality technique on time scales, we obtain the existence of almost periodic solutions for this networks. Then, by constructing a suitable Lyapunov function, we obtain that the drive-response structure of complex-valued neural networks with almost periodic coefficients can realize the global exponential synchronization. Our results are completely new. Finally, we give an example to illustrate the feasibility of our results.
- Complex-valued neural networks /
- synchronization /
- impulsive effects /
- time scales
MSC: 34C27, 34D06, 92B20

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References

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