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Author Choi, Jun Won ♦ Shim, Byonghyo ♦ Singer, Andrew C. ♦ Cho, Nam Ik
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract In this paper, we present a maximum likelihood-based error correction (ML-EC) technique which achieves significant power savings in digital filtering. Although voltage overscaling (VOS) can achieve high energy efficiency, it can introduce “soft errors ” which severely degrade the performance of the filter. The proposed scheme detects, estimates and corrects these soft errors via an ML-based algorithm that achieves up to 47 % power savings without any SNR loss and up to 60 % power savings with a 1.5 dB SNR loss for an example case study of a frequency-selective low-pass filter. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study