NDLI: Low memory-cost scramble methods for constructing deterministic CS matrix

Content Provider	IEEE Xplore Digital Library
Author	Jie-Fang Zhang Jing Geng Yu-Min Lin An-Yeu Wu
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan (Jie-Fang Zhang; Jing Geng) \|\| Grad. Inst. of Electron. Eng., Nat. Taiwan Univ., Taipei, Taiwan (Yu-Min Lin; An-Yeu Wu)
Abstract	Compressed sensing (CS) is an emerging field in data acquisition that measures signal below the Nyquist rate through sensing matrix. Random matrices have been regarded as optimal sensing matrices in CS but cost too much memory space. Structured matrices are then proposed to decrease memory cost by deterministic sensing. Nevertheless, the recovery suffers from severe degradation when using these structured matrices as sensing matrices for signals which are sparse under specific domain. In this paper, we propose two scramble methods to compensate the performance loss of structured matrices under alternative region of interest. The proposed predefined scramble matrix (PSM) method is able to match the guarantee region of recovery of Gaussian random matrices. The PSM method requires as much memory space as the structured matrices and has sub-optimal recovery performance. On the other hand, the proposed built-in location selection (BLS) method is able to approximate the whole region of recovery of Gaussian random matrices. The BLS method can achieve optimal recovery performance with some extra memory and logic cost than PSM method. Compared to 128 × 512 Gaussian sensing matrix, the PSM method and the BLS method can reduce 98.4% and 96% of the memory cost, respectively.
Starting Page	1
Ending Page	6
File Size	10293989
Page Count	6
File Format	PDF
e-ISBN	9781467396042
DOI	10.1109/SiPS.2015.7345004
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensors Sparse matrices Coherence Matrices Degradation Simulation Compressed sensing deterministic sensing matrix compressed sensing(CS) structured matrix
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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