Low power real-time data acquisition using compressive sensing

Linda S. Powers; Yiming Zhang; Kemeng Chen; Huiqing Pan; Wo-Tak Wu; Peter W. Hall; Jerrie V. Fairbanks; Radik Nasibulin; Janet M. Roveda

doi:10.1117/12.2263220

18 May 2017 Low power real-time data acquisition using compressive sensing

Linda S. Powers, Yiming Zhang, Kemeng Chen, Huiqing Pan, Wo-Tak Wu, Peter W. Hall, Jerrie V. Fairbanks, Radik Nasibulin, Janet M. Roveda

Author Affiliations +

Proceedings Volume 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX; 101940C (2017) https://doi.org/10.1117/12.2263220
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

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.

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Linda S. Powers, Yiming Zhang, Kemeng Chen, Huiqing Pan, Wo-Tak Wu, Peter W. Hall, Jerrie V. Fairbanks, Radik Nasibulin, and 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); https://doi.org/10.1117/12.2263220

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