脉冲型惯性双向联想记忆神经网络新解

Chaouki AOUITI; Mahjouba Ben REZEG; 曹阳

doi:10.1631/FITEE.1900181

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脉冲型惯性双向联想记忆神经网络新解

复杂系统和网络及其应用专辑 | Updated：2022-05-19

- 脉冲型惯性双向联想记忆神经网络新解
- New results on impulsive type inertial bidirectional associative memory neural networks
- 信息与电子工程前沿（英文） 2020年21卷第2期页码：324-339
- Affiliations：
  
  Department of Mathematics, the University of Carthage, Zarzouna 7021, Bizerta, Tunisia
  School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China
  Department of Mechanical Engineering, the University of Hong Kong, Pokfulam, Hong Kong, China
- Author bio：
  
  [ "Chaouki AOUITI, E-mail: chaouki.aouiti@fsb.rnu.tn" ]
  [ "Mahjouba Ben REZEG, E-mail: mahjouba.benrezek@fsb.rnu.tn" ]
  Yang CAO, E-mail: caoyeacy@gmail.com
- Funds：
- DOI：10.1631/FITEE.1900181
  中图分类号： TP183;O175
- 纸质出版日期：2020-02，
  
  收稿日期：2019-04-07，
  
  修回日期：2020-01-07，
- Accepted：
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Chaouki AOUITI, Mahjouba Ben REZEG, 曹阳. 脉冲型惯性双向联想记忆神经网络新解[J]. 信息与电子工程前沿（英文）, 2020,21(2):324-339.

AOUITI CHAOUKI, BEN REZEG MAHJOUBA, CAO YANG. New results on impulsive type inertial bidirectional associative memory neural networks. [J]. Frontiers of information technology & electronic engineering, 2020, 21(2): 324-339.
Chaouki AOUITI, Mahjouba Ben REZEG, 曹阳. 脉冲型惯性双向联想记忆神经网络新解[J]. 信息与电子工程前沿（英文）, 2020,21(2):324-339. DOI： 10.1631/FITEE.1900181.

AOUITI CHAOUKI, BEN REZEG MAHJOUBA, CAO YANG. New results on impulsive type inertial bidirectional associative memory neural networks. [J]. Frontiers of information technology & electronic engineering, 2020, 21(2): 324-339. DOI： 10.1631/FITEE.1900181.

摘要

探究了具有混合时滞和脉冲效应的惯性双向联想记忆神经网络。该研究为类似系统的反周期解的存在性、唯一性和全局指数稳定性提供了新的实用条件。使用微分不等式技术证明我们的主要结果，并给出一个仿真算例证明新结果的有效性。

Abstract

This paper is concerned with inertial bidirectional associative memory neural networks with mixed delays and impulsive effects. New and practical conditions are given to study the existence

uniqueness

and global exponential stability of anti-periodic solutions for the suggested system. We use differential inequality techniques to prove our main results. Finally

we give an illustrative example to demonstrate the effectiveness of our new results.

关键词

惯性神经网络反周期解全局指数稳定脉冲时变延迟双向联想记忆

Keywords

Inertial neural networksAnti-periodic solutionsGlobal exponential stabilityImpulsive effectTime-varying delayBidirectional associative memory

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