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, Meiling Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationMicro- and Nanotechnology Sensors, Systems, and Applications IX
PublisherSPIE
Volume10194
ISBN (Electronic)9781510608894
DOIs
StatePublished - 2017
EventMicro- and Nanotechnology Sensors, Systems, and Applications IX 2017 - Anaheim, United States
Duration: Apr 9 2017Apr 13 2017

Other

OtherMicro- and Nanotechnology Sensors, Systems, and Applications IX 2017
CountryUnited States
CityAnaheim
Period4/9/174/13/17

Fingerprint

Compressive Sensing
Data Acquisition
data acquisition
Data acquisition
Real-time
High Speed
sampling
high speed
analogs
Sampling
Analogue
Level Crossing
Adaptive Design
Digitization
data compression
information systems
Analog to digital conversion
Data compression
Data Compression
Instrumentation

Keywords

  • Adaptive Design for Information
  • Compressive sensing
  • low power
  • real-time data acquisition

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Powers, L. S., Zhang, Y., Chen, K., Pan, H., Wu, W. T., Hall, P. W., ... Wang, M. (2017). Low power real-time data acquisition using compressive sensing. In Micro- and Nanotechnology Sensors, Systems, and Applications IX (Vol. 10194). [101940C] SPIE. https://doi.org/10.1117/12.2263220

Low power real-time data acquisition using compressive sensing. / Powers, Linda S; Zhang, Yiming; Chen, Kemeng; Pan, Huiqing; Wu, Wo Tak; Hall, Peter W.; Fairbanks, Jerrie V.; Nasibulin, Radik; Wang, Meiling.

Micro- and Nanotechnology Sensors, Systems, and Applications IX. Vol. 10194 SPIE, 2017. 101940C.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Powers, LS, Zhang, Y, Chen, K, Pan, H, Wu, WT, Hall, PW, Fairbanks, JV, Nasibulin, R & Wang, M 2017, Low power real-time data acquisition using compressive sensing. in Micro- and Nanotechnology Sensors, Systems, and Applications IX. vol. 10194, 101940C, SPIE, Micro- and Nanotechnology Sensors, Systems, and Applications IX 2017, Anaheim, United States, 4/9/17. https://doi.org/10.1117/12.2263220
Powers LS, Zhang Y, Chen K, Pan H, Wu WT, Hall PW et al. Low power real-time data acquisition using compressive sensing. In Micro- and Nanotechnology Sensors, Systems, and Applications IX. Vol. 10194. SPIE. 2017. 101940C https://doi.org/10.1117/12.2263220
Powers, Linda S ; Zhang, Yiming ; Chen, Kemeng ; Pan, Huiqing ; Wu, Wo Tak ; Hall, Peter W. ; Fairbanks, Jerrie V. ; Nasibulin, Radik ; Wang, Meiling. / Low power real-time data acquisition using compressive sensing. Micro- and Nanotechnology Sensors, Systems, and Applications IX. Vol. 10194 SPIE, 2017.
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