Convergence of sparse coding based on KKT conditions

doi:10.13878/j.cnki.jnuist.2020.03.015

2025-6-3- 8

Home > Archive>Volume 12, Issue 3, 2020 >360-363. DOI:10.13878/j.cnki.jnuist.2020.03.015

Convergence of sparse coding based on KKT conditions
DOI:
                        10.13878/j.cnki.jnuist.2020.03.015
                    
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                        TAO YingyinTAO Yingyin
Key Laboratory of Intelligent Information Processing and Control of Chongqing Municipal Institutions of Higher Education, Chongqing Three Gorges University, Chongqing 404100
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YANG YiYANG Yi
Key Laboratory of Intelligent Information Processing and Control of Chongqing Municipal Institutions of Higher Education, Chongqing Three Gorges University, Chongqing 404100
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DAI XiangguangDAI Xiangguang
Key Laboratory of Intelligent Information Processing and Control of Chongqing Municipal Institutions of Higher Education, Chongqing Three Gorges University, Chongqing 404100
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SU XiaojieSU Xiaojie
College of Automation, Chongqing University, Chongqing 400044
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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.

Key words:KKT conditions;convergence;non-convex non-mooth;sparse coding

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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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Received:February 26,2020
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Online: July 07,2020
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