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联合子空间模型的模拟信息转换器研究
刘铁锋
中国科学院沈阳自动化研究所
摘要:
依据Shannon采样定理的模拟-数字转换器(Analog-to-Digital Convertor,ADC)越来越难以满足对高频、宽频信号的采样需求,为实现低速率采样同时缓解数据传输、存储及处理的压力,基于亚Nyquist采样的模拟信息转换器(Analog-to-Information Convertor,AIC)成为研究热点。首先概述了压缩感知(Compressed Sensing,CS)理论、单向量空间(Single Vector Space,SVS)和联合子空间(Union of Subspaces,UoS)采样理论,着重总结和对比了几种符合UoS模型的信号AIC采样架构及恢复算法,最后展望了AIC未来研究方向。
关键词:  模拟信息转换器 压缩感知 联合子空间 亚Nyquist采样
DOI:10.13195/j.kzyjc.2018.1273
分类号:TP3-05
基金项目:
Research on Analog-to-Information Converter Based on Union of Subspaces Model
liutiefeng
Shenyang Institute of Automation Chinese Academy of Sciences
Abstract:
Traditional analog-to-digital convertors (ADC) based on the Shannon sampling theorem can hardly satisfy the sampling requirements for high-frequency and wide-band signals. For the purpose of sampling rate reducing and data transmission, storage, process relaxing, new analog-to-information convertors (AIC) based on sub-Nyquist sampling methods have drawn many researchers’ attention in recent years. Compressed sensing (CS) theory, single vector space (SVS) and union of subspaces (UoS) sampling theory are introduced. Based on the UoS signal model, an emphasis on AIC sampling architectures and recovery algorithms are summarized and compared. Finally, future research directions are given.
Key words:  analog-to-information convertor (AIC) compressed sensing (CS) union of subspaces (UoS) sub-Nyquist sampling

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