{"title":"稀疏Volterra系统的辨识：一种几乎正交匹配寻踪方法","authors":"Changming Cheng;Er-Wei Bai;Zhike Peng","doi":"10.1109/TAC.2021.3070027","DOIUrl":null,"url":null,"abstract":"This article considers identification of sparse Volterra systems. A method based on the almost orthogonal matching pursuit (AOMP) is proposed. The AOMP algorithm allows one to estimate one nonzero coefficient at a time until all nonzero coefficients are found without losing the optimality and the sparsity, thus avoiding the curse of dimensionality often encountered in Volterra system identification.","PeriodicalId":13201,"journal":{"name":"IEEE Transactions on Automatic Control","volume":"67 4","pages":"2027-2032"},"PeriodicalIF":6.2000,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TAC.2021.3070027","citationCount":"2","resultStr":"{\"title\":\"Identification of Sparse Volterra Systems: An Almost Orthogonal Matching Pursuit Approach\",\"authors\":\"Changming Cheng;Er-Wei Bai;Zhike Peng\",\"doi\":\"10.1109/TAC.2021.3070027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article considers identification of sparse Volterra systems. A method based on the almost orthogonal matching pursuit (AOMP) is proposed. The AOMP algorithm allows one to estimate one nonzero coefficient at a time until all nonzero coefficients are found without losing the optimality and the sparsity, thus avoiding the curse of dimensionality often encountered in Volterra system identification.\",\"PeriodicalId\":13201,\"journal\":{\"name\":\"IEEE Transactions on Automatic Control\",\"volume\":\"67 4\",\"pages\":\"2027-2032\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2021-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TAC.2021.3070027\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Automatic Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/9392313/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Automatic Control","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/9392313/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Identification of Sparse Volterra Systems: An Almost Orthogonal Matching Pursuit Approach
This article considers identification of sparse Volterra systems. A method based on the almost orthogonal matching pursuit (AOMP) is proposed. The AOMP algorithm allows one to estimate one nonzero coefficient at a time until all nonzero coefficients are found without losing the optimality and the sparsity, thus avoiding the curse of dimensionality often encountered in Volterra system identification.
期刊介绍：
In the IEEE Transactions on Automatic Control, the IEEE Control Systems Society publishes high-quality papers on the theory, design, and applications of control engineering. Two types of contributions are regularly considered:
1) Papers: Presentation of significant research, development, or application of control concepts.
2) Technical Notes and Correspondence: Brief technical notes, comments on published areas or established control topics, corrections to papers and notes published in the Transactions.
In addition, special papers (tutorials, surveys, and perspectives on the theory and applications of control systems topics) are solicited.
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