基于KKT条件的稀疏编码算法收敛性研究
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O232

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重庆市高校市级重点实验室资助项目([2017]3);重庆市发展和改革委员会资助项目(2017[1007]);重庆市教委科技研究项目(KJQN201901203,KJQN201901218,KJ1710248);重庆市自然科学基金(cstc2019jcyj-bshX0101)


Convergence of sparse coding based on KKT conditions
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    摘要:

    本文提出了基于KKT条件的稀疏编码算法.首先,将非凸非光滑的稀疏编码问题分解成两个凸非光滑问题;然后,巧妙地运用两个矩阵使两个凸非光滑问题转换成三个光滑凸优化问题,并通过KKT条件对三个问题进行求解,再通过凸优化理论证明三个问题在其对应规则下是非增的.最后,实验结果验证了算法的收敛性.

    Abstract:

    This paper proposes a sparse coding algorithm based on KKT conditions.Firstly,the non-convex non-smooth sparse coding problem is decomposed into two convex non-smooth problems.Secondly,the two convex non-smooth problems are skillfully transformed into three smooth convex optimization problems by using two matrices.Finally,the three problems are solved by KKT conditions.In addition,we prove the convergence of the algorithm.Meanwhile,experimental simulation shows the convergence of the algorithm.

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陶盈吟,杨仪,代祥光,苏晓杰.基于KKT条件的稀疏编码算法收敛性研究[J].南京信息工程大学学报(自然科学版),2020,12(3):360-363
TAO Yingyin, YANG Yi, DAI Xiangguang, SU Xiaojie. Convergence of sparse coding based on KKT conditions[J]. Journal of Nanjing University of Information Science & Technology, 2020,12(3):360-363

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  • 收稿日期:2020-02-26
  • 在线发布日期: 2020-07-07

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