{"title":"不连续收缩算子的连续松弛:近端包合与转换","authors":"Masahiro Yukawa","doi":"10.1109/OJSP.2025.3579646","DOIUrl":null,"url":null,"abstract":"We present a principled way of deriving a continuous relaxation of a given discontinuous shrinkage operator, which is based on two fundamental results, proximal inclusion and conversion. Using our results, the discontinuous operator is converted, via double inversion, to a continuous operator; more precisely, the associated “set-valued” operator is converted to a “single-valued” Lipschitz continuous operator. The first illustrative example is the firm shrinkage operator which can be derived as a continuous relaxation of the hard shrinkage operator. We also derive a new operator as a continuous relaxation of the discontinuous shrinkage operator associated with the so-called reverse ordered weighted <inline-formula><tex-math>$\\ell _{1}$</tex-math></inline-formula> (ROWL) penalty. Numerical examples demonstrate potential advantages of the continuous relaxation.","PeriodicalId":73300,"journal":{"name":"IEEE open journal of signal processing","volume":"6 ","pages":"753-767"},"PeriodicalIF":2.9000,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11034740","citationCount":"0","resultStr":"{\"title\":\"Continuous Relaxation of Discontinuous Shrinkage Operator: Proximal Inclusion and Conversion\",\"authors\":\"Masahiro Yukawa\",\"doi\":\"10.1109/OJSP.2025.3579646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a principled way of deriving a continuous relaxation of a given discontinuous shrinkage operator, which is based on two fundamental results, proximal inclusion and conversion. Using our results, the discontinuous operator is converted, via double inversion, to a continuous operator; more precisely, the associated “set-valued” operator is converted to a “single-valued” Lipschitz continuous operator. The first illustrative example is the firm shrinkage operator which can be derived as a continuous relaxation of the hard shrinkage operator. We also derive a new operator as a continuous relaxation of the discontinuous shrinkage operator associated with the so-called reverse ordered weighted <inline-formula><tex-math>$\\\\ell _{1}$</tex-math></inline-formula> (ROWL) penalty. Numerical examples demonstrate potential advantages of the continuous relaxation.\",\"PeriodicalId\":73300,\"journal\":{\"name\":\"IEEE open journal of signal processing\",\"volume\":\"6 \",\"pages\":\"753-767\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11034740\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE open journal of signal processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11034740/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE open journal of signal processing","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11034740/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
摘要
我们提出了一个原则性的方法来推导一个给定的不连续收缩算子的连续松弛,这是基于两个基本结果,近端包含和转换。利用我们的结果,通过双反演,不连续算子被转换为连续算子;更准确地说,相关的“集值”算子被转换为“单值”Lipschitz连续算子。第一个说明性的例子是坚固收缩算子,它可以作为硬收缩算子的连续松弛而导出。我们还推导了一个新的算子,作为与所谓的反向有序加权$\ well _{1}$ (ROWL)惩罚相关的不连续收缩算子的连续松弛。数值算例表明了连续松弛的潜在优势。
Continuous Relaxation of Discontinuous Shrinkage Operator: Proximal Inclusion and Conversion
We present a principled way of deriving a continuous relaxation of a given discontinuous shrinkage operator, which is based on two fundamental results, proximal inclusion and conversion. Using our results, the discontinuous operator is converted, via double inversion, to a continuous operator; more precisely, the associated “set-valued” operator is converted to a “single-valued” Lipschitz continuous operator. The first illustrative example is the firm shrinkage operator which can be derived as a continuous relaxation of the hard shrinkage operator. We also derive a new operator as a continuous relaxation of the discontinuous shrinkage operator associated with the so-called reverse ordered weighted $\ell _{1}$ (ROWL) penalty. Numerical examples demonstrate potential advantages of the continuous relaxation.