中国科学院沈阳自动化研究所机构知识库
Advanced  
SIA OpenIR  > 机器人学研究室  > 会议论文
题名: Maximum length sequence encoded Hadamard measurement paradigm for compressed sensing
作者: Qin SJ(秦书嘉) ; Bi S(毕盛) ; Xi N(席宁)
作者部门: 机器人学研究室
会议名称: 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2014
会议日期: July 8-11, 2014
会议地点: Besancon, France
会议录: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
会议录出版者: Institute of Electrical and Electronics Engineers Inc.
会议录出版地: New York
出版日期: 2014
页码: 1151-1156
收录类别: CPCI(ISTP) ; EI
ISBN号: 9781479957361
关键词: Artificial intelligence ; Computer programming ; Hadamard matrices ; Hadamard transforms ; Intelligent mechatronics ; Medical imaging ; Spectroscopy
摘要: The development of compressed sensing technology has greatly facilitated its applications in many fields, such as medical imaging, multi-sensor and distributed sensing, coding theory, hyper-spectral imaging, and machine learning. Among these applications, the permuted Walsh-Hadamard matrices are frequently chosen for modeling real-world measurements that are limited to binary entry states by special structure (one typical example is the digital mirror device in singlepixel cameras) because the fast Walsh-Hadamard transform can efficiently calculate its multiplications; however, for a large-scale problem, the Walsh-Hadamard matrix would become unacceptably large to be stored in advance. To eliminate this defect, this paper proposes a maximum length sequence encoded Hadamard measurement paradigm that can be simply realized on chip without any usage of external memory, and proves this method can degenerate to a special permutation of the sequence ordered Walsh-Hadamard matrix so that the fast Walsh-Hadamard transform keeps feasible. Simulations show that compared with the conventional permuted Walsh-Hadamard matrix, the proposed one can emerge from the limit of external memory without losing much randomness performance in the measurement basis required by compressed sensing. © 2014 IEEE.
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/15155
Appears in Collections:机器人学研究室_会议论文

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
Maximum length sequence encoded Hadamard measurement paradigm for compressed sensing.pdf(1373KB)----开放获取View Download
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Qin SJ(秦书嘉)]'s Articles
[Bi S(毕盛)]'s Articles
[Xi N(席宁)]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Qin SJ(秦书嘉)]‘s Articles
[Bi S(毕盛)]‘s Articles
[Xi N(席宁)]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: Maximum length sequence encoded Hadamard measurement paradigm for compressed sensing.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2016  中国科学院沈阳自动化研究所 - Feedback
Powered by CSpace