A Gradient-Enhanced l(1) Approach for the Recovery of Sparse Trigonometric Polynomials
文献类型：期刊论文
| 作者 | Xu, Zhiqiang ; Zhou, Tao
|
| 刊名 | COMMUNICATIONS IN COMPUTATIONAL PHYSICS
 |
| 出版日期 | 2018-07-01 |
| 卷号 | 24期号:1页码:286-308 |
| 关键词 | Gradient-enhanced l(1) minimization compressed sensing sparse Fourier expansions restricted isometry property mutual incoherence |
| ISSN号 | 1815-2406 |
| DOI | 10.4208/cicp.OA-2018-0006 |
| 英文摘要 | In this paper, we discuss a gradient-enhanced l(1) approach for the recovery of sparse Fourier expansions. By gradient-enhanced approaches we mean that the directional derivatives along given vectors are utilized to improve the sparse approximations. We first consider the case where both the function values and the directional derivatives at sampling points are known. We show that, under some mild conditions, the inclusion of the derivatives information can indeed decrease the coherence of measurement matrix, and thus leads to the improved the sparse recovery conditions of the l(1) minimization. We also consider the case where either the function values or the directional derivatives are known at the sampling points, in which we present a sufficient condition under which the measurement matrix satisfies RIP, provided that the samples are distributed according to the uniform measure. This result shows that the derivatives information plays a similar role as that of the function values. Several numerical examples are presented to support the theoretical statements. Potential applications to function (Hermite-type) interpolations and uncertainty quantification are also discussed. |
| 资助项目 | NSFC[91630203] ; NSFC[11422113] ; NSFC[11331012] ; NSFC[11688101] ; National Basic Research Program of China (973 Program)[2015CB856000] ; NSF of China[91630203] ; NSF of China[11688101] ; NSF of China[91630312] ; NSF of China[11571351] ; NSF of China[11731006] ; science challenge project[TZ2018001] ; NCMIS ; youth innovation promotion association (CAS) |
| WOS研究方向 | Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:000455953800014 |
| 出版者 | GLOBAL SCIENCE PRESS |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/32279]  |
| 专题 | 计算数学与科学工程计算研究所 |
| 通讯作者 | Zhou, Tao |
| 作者单位 | Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math, LSEC, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Zhiqiang,Zhou, Tao. A Gradient-Enhanced l(1) Approach for the Recovery of Sparse Trigonometric Polynomials[J]. COMMUNICATIONS IN COMPUTATIONAL PHYSICS,2018,24(1):286-308. |
| APA | Xu, Zhiqiang,&Zhou, Tao.(2018).A Gradient-Enhanced l(1) Approach for the Recovery of Sparse Trigonometric Polynomials.COMMUNICATIONS IN COMPUTATIONAL PHYSICS,24(1),286-308. |
| MLA | Xu, Zhiqiang,et al."A Gradient-Enhanced l(1) Approach for the Recovery of Sparse Trigonometric Polynomials".COMMUNICATIONS IN COMPUTATIONAL PHYSICS 24.1(2018):286-308. |
入库方式： OAI收割
来源：数学与系统科学研究院
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