We propose a low-power filtering algorithm developed via the soft DSP framework. Soft DSP refers to scaling the supply voltage of a DSP implementation beyond the voltage required to match its critical path delay to the throughput. This deliberate introduction of input-dependent errors leads to degradation in the algorithmic performance, which is then compensated for via algorithmic error-control schemes. The proposed error-control schemes, based on forward/backward linear prediction, provides improved performance over the ones proposed in the past by exploiting correlation in both leading and trailing samples with a latency penalty. It is shown that (a) the proposed scheme provides 60-80% reduction in energy dissipation over that achieved via conventional voltage scaling and (b) for the same algorithmic performance, the overhead involved in the proposed algorithm is more than 50% smaller than existing schemes for medium bandwidth filters.
|Title of host publication
|Design and Implementation of Signal Processing SystemNeural Networks for Signal Processing Signal Processing EducationOther Emerging Applications of Signal ProcessingSpecial Sessions
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 2000
|25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey
Duration: Jun 5 2000 → Jun 9 2000
|ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
|25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000
|6/5/00 → 6/9/00
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering