@inproceedings{b3446a9d70154f3eae06fbba37747997,
title = "An energy-aware framework for cascaded detection algorithms",
abstract = "Low-power, scalable detection systems require aggressive techniques to achieve energy efficiency. Algorithmic methods that can reduce energy consumption by compromising performance are known as being energy-aware. We propose a framework that imposes energy-awareness on cascaded detection algorithms. This is done by setting the detectors' thresholds to make a systematic trade-off between energy consumption and detection performance. The thresholds are determined by solving our proposed energy-constrained version of the Neyman-Pearson detection criterion. Our proposed optimization method systematically determines the energy-optimal thresholds and dynamically adjusts to time-varying system requirements. This framework is applied to a two-stage cascade, and simulations show that our energy-aware cascaded detectors outperform an energy-aware detection algorithm based on incremental refinement. Finally, combining our framework with incremental refinement reveals a promising approach to the design of energy-efficient detection systems.",
keywords = "Energy-aware, Incremental refinement, Passive vigilance, Scalable systems, Signal detection",
author = "Jun, {David M.} and Jones, {Douglas L.}",
note = "Copyright: Copyright 2011 Elsevier B.V., All rights reserved.; 2010 IEEE Workshop on Signal Processing Systems, SiPS 2010 ; Conference date: 06-10-2010 Through 08-10-2010",
year = "2010",
doi = "10.1109/SIPS.2010.5624823",
language = "English (US)",
isbn = "9781424489336",
series = "IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation",
pages = "1--6",
booktitle = "2010 IEEE Workshop on Signal Processing Systems, SiPS 2010 - Proceedings",
}