用Python介绍压缩感知

IF 0.7 4区计算机科学 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC

IEICE Transactions on Communications Pub Date : 2023-01-01 DOI:10.1587/transcom.2023ebi0002

Masaaki Nagahara

{"title":"用Python介绍压缩感知","authors":"Masaaki Nagahara","doi":"10.1587/transcom.2023ebi0002","DOIUrl":null,"url":null,"abstract":"SUMMARY Compressed sensing is a rapidly growing research field in signal and image processing, machine learning, statistics, and systems control. In this survey paper, we provide a review of the theoretical foundations of compressed sensing and present state-of-the-art algorithms for solving the corresponding optimization problems. Additionally, we discuss several practical applications of compressed sensing, such as group testing, sparse system identification, and sparse feedback gain design, and demonstrate their effectiveness through Python programs. This survey paper aims to contribute to the advancement of compressed sensing research and its practical applications in various scientific disciplines.","PeriodicalId":50385,"journal":{"name":"IEICE Transactions on Communications","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Introduction to Compressed Sensing with Python\",\"authors\":\"Masaaki Nagahara\",\"doi\":\"10.1587/transcom.2023ebi0002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"SUMMARY Compressed sensing is a rapidly growing research field in signal and image processing, machine learning, statistics, and systems control. In this survey paper, we provide a review of the theoretical foundations of compressed sensing and present state-of-the-art algorithms for solving the corresponding optimization problems. Additionally, we discuss several practical applications of compressed sensing, such as group testing, sparse system identification, and sparse feedback gain design, and demonstrate their effectiveness through Python programs. This survey paper aims to contribute to the advancement of compressed sensing research and its practical applications in various scientific disciplines.\",\"PeriodicalId\":50385,\"journal\":{\"name\":\"IEICE Transactions on Communications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEICE Transactions on Communications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1587/transcom.2023ebi0002\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEICE Transactions on Communications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1587/transcom.2023ebi0002","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}

引用次数: 0

摘要

压缩感知是信号和图像处理、机器学习、统计学和系统控制等领域快速发展的研究领域。在这篇调查论文中，我们提供了压缩感知的理论基础的回顾，并提出了解决相应的优化问题的最新算法。此外，我们还讨论了压缩感知的几个实际应用，如组测试、稀疏系统识别和稀疏反馈增益设计，并通过Python程序演示了它们的有效性。本文旨在促进压缩感知的研究及其在各个科学学科中的实际应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Introduction to Compressed Sensing with Python

SUMMARY Compressed sensing is a rapidly growing research field in signal and image processing, machine learning, statistics, and systems control. In this survey paper, we provide a review of the theoretical foundations of compressed sensing and present state-of-the-art algorithms for solving the corresponding optimization problems. Additionally, we discuss several practical applications of compressed sensing, such as group testing, sparse system identification, and sparse feedback gain design, and demonstrate their effectiveness through Python programs. This survey paper aims to contribute to the advancement of compressed sensing research and its practical applications in various scientific disciplines.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

IEICE Transactions on Communications 工程技术-电信学

CiteScore

1.40

自引率

28.60%

发文量

101

审稿时长

3.7 months

期刊介绍： The IEICE Transactions on Communications is an all-electronic journal published occasionally by the Institute of Electronics, Information and Communication Engineers (IEICE) and edited by the Communications Society in IEICE. The IEICE Transactions on Communications publishes original, peer-reviewed papers that embrace the entire field of communications, including: - Fundamental Theories for Communications - Energy in Electronics Communications - Transmission Systems and Transmission Equipment for Communications - Optical Fiber for Communications - Fiber-Optic Transmission for Communications - Network System - Network - Internet - Network Management/Operation - Antennas and Propagation - Electromagnetic Compatibility (EMC) - Wireless Communication Technologies - Terrestrial Wireless Communication/Broadcasting Technologies - Satellite Communications - Sensing - Navigation, Guidance and Control Systems - Space Utilization Systems for Communications - Multimedia Systems for Communication