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Conference Paper: Maximum length sequence encoded Hadamard measurement paradigm for compressed sensing

TitleMaximum length sequence encoded Hadamard measurement paradigm for compressed sensing
Authors
Issue Date2014
Citation
IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM, 2014, p. 1151-1156 How to Cite?
AbstractThe 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.
Persistent Identifierhttp://hdl.handle.net/10722/213429

 

DC FieldValueLanguage
dc.contributor.authorQin, Shujia-
dc.contributor.authorBi, Sheng-
dc.contributor.authorXi, Ning-
dc.date.accessioned2015-07-28T04:07:15Z-
dc.date.available2015-07-28T04:07:15Z-
dc.date.issued2014-
dc.identifier.citationIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM, 2014, p. 1151-1156-
dc.identifier.urihttp://hdl.handle.net/10722/213429-
dc.description.abstractThe 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.-
dc.languageeng-
dc.relation.ispartofIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM-
dc.titleMaximum length sequence encoded Hadamard measurement paradigm for compressed sensing-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1109/AIM.2014.6878236-
dc.identifier.scopuseid_2-s2.0-84906719062-
dc.identifier.spage1151-
dc.identifier.epage1156-

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