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《山东大学学报(理学版)》 ›› 2018, Vol. 53 ›› Issue (12): 90-98.doi: 10.6040/j.issn.1671-9352.0.2017.627

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求解具有约束的l1-范数问题的神经网络模型

李翠平,高兴宝*   

  1. 陕西师范大学数学与信息科学学院, 陕西 西安 710062
  • 出版日期:2018-12-20 发布日期:2018-12-18
  • 作者简介:李翠平(1982— ), 女, 博士研究生, 讲师, 研究方向为最优化方法(神经网络模型). E-mail:cuipli@126.com*通信作者简介:高兴宝(1966— ), 男, 博士, 教授, 博士生导师, 研究方向为智能优化方法、最优化理论与算法. E-mail:xinbaog@snnu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(61273311,61603235)

A neural network for solving l1-norm problems with constraints

LI Cui-ping, GAO Xing-bao*   

  1. School of Mathematics and Information Science, Shaanxi Normal University, Xian 710062, Shaanxi, China
  • Online:2018-12-20 Published:2018-12-18

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摘要： 提出了一个解约束最小 l1-范数问题的单层神经网络模型。与已有神经网络模型相比,提出的模型所需神经元数少且层数少。通过引入 Lyapunov 函数,证明了该模型的稳定性和收敛性。数值试验结果表明所提出的模型具有良好的性能。

关键词: l1-范数问题, 神经网络, 单层, 稳定性

Abstract: This paper presents a one-layer neural network model for solving l1-norm problems with constraints. Compared with some existing neural network models, the proposed model needs fewer neurons and has a simpler structure. The stability and convergence of the proposed model are proved by introducing a Lyapunov function. Some simulation examples are used to illustrate its validity and transient behaviors.

Key words: l1-norm problem, neural network, one-layer, stability

中图分类号: 

  • O241.6
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