AuthorPowers, Linda S.
Hall, Peter W.
Fairbanks, Jerrie V.
Roveda, Janet M.
AffiliationUniv Arizona, Dept Elect & Comp Engn
Univ Arizona, Biomed Engn Grad Interdisciplinary Program
MetadataShow full item record
PublisherSPIE-INT SOC OPTICAL ENGINEERING
CitationLinda S. Powers, Yiming Zhang, Kemeng Chen, Huiqing Pan, Wo-Tak Wu, Peter W. Hall, Jerrie V. Fairbanks, Radik Nasibulin, Janet M. Roveda, "Low power real-time data acquisition using compressive sensing", Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 101940C (18 May 2017); doi: 10.1117/12.2263220; http://dx.doi.org/10.1117/12.2263220
Rights© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
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AbstractNew possibilit ies 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 . 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.
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