New 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 [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.
Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/626011 |
Date | 18 May 2017 |
Creators | Powers, Linda S., Zhang, Yiming, Chen, Kemeng, Pan, Huiqing, Wu, Wo-Tak, Hall, Peter W., Fairbanks, Jerrie V., Nasibulin, Radik, Roveda, Janet M. |
Contributors | Univ Arizona, Dept Elect & Comp Engn, Univ Arizona, Biomed Engn Grad Interdisciplinary Program, The Univ. of Arizona (United States), The Univ. of Arizona (United States), The Univ. of Arizona (United States), The Univ. of Arizona (United States), The Univ. of Arizona (United States), The Univ. of Arizona (United States), The Univ. of Arizona (United States), The Univ. of Arizona (United States), The Univ. of Arizona (United States) |
Publisher | SPIE-INT SOC OPTICAL ENGINEERING |
Source Sets | University of Arizona |
Language | English |
Detected Language | English |
Type | Article |
Rights | © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). |
Relation | http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2263220 |
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