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 over-scaling (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.
| Original language | English |
|---|---|
| Title of host publication | 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | IV733-IV736 |
| ISBN (Print) | 0780388747, 9780780388741 |
| DOIs | |
| Publication status | Published - 2005 |
| Event | 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States Duration: 2005 Mar 18 → 2005 Mar 23 |
Publication series
| Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
|---|---|
| Volume | IV |
| ISSN (Print) | 1520-6149 |
Other
| Other | 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 |
|---|---|
| Country/Territory | United States |
| City | Philadelphia, PA |
| Period | 05/3/18 → 05/3/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering
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