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Proceedings Paper

Low power real-time data acquisition using compressive sensing
Author(s): Linda S. Powers; Yiming Zhang; Kemeng Chen; Huiqing Pan; Wo-Tak Wu; Peter W. Hall; Jerrie V. Fairbanks; Radik Nasibulin; Janet M. Roveda
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Paper Abstract

New possibilities exist for the development of novel hardware/software platforms havin g fast data acquisition capability with low power requirements. One application is a high speed Adaptive Design for Information (ADI) system that combines the advantages of feature-based data compression, low power nanometer CMOS technology, and stream computing [1]. We have developed a compressive sensing (CS) algorithm which linearly reduces the data at the analog front end, an approach which uses analog designs and computations instead of smaller feature size transistors for higher speed and lower power. A level-crossing sampling approach replaces Nyquist sampling. With an in-memory design, the new compressive sensing based instrumentation performs digitization only when there is enough variation in the input and when the random selection matrix chooses this input.

Paper Details

Date Published: 18 May 2017
PDF: 6 pages
Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 101940C (18 May 2017); doi: 10.1117/12.2263220
Show Author Affiliations
Linda S. Powers, The Univ. of Arizona (United States)
Yiming Zhang, The Univ. of Arizona (United States)
Kemeng Chen, The Univ. of Arizona (United States)
Huiqing Pan, The Univ. of Arizona (United States)
Wo-Tak Wu, The Univ. of Arizona (United States)
Peter W. Hall, The Univ. of Arizona (United States)
Jerrie V. Fairbanks, The Univ. of Arizona (United States)
Radik Nasibulin, The Univ. of Arizona (United States)
Janet M. Roveda, The Univ. of Arizona (United States)


Published in SPIE Proceedings Vol. 10194:
Micro- and Nanotechnology Sensors, Systems, and Applications IX
Thomas George; Achyut K. Dutta; M. Saif Islam, Editor(s)

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