{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/18395"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/18395","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"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. The cascade architecture is known for being energy-efficient, but without proper operation can end up being energy-inefficient in practice. In this thesis, we propose a framework that imposes energy-awareness on cascaded detection algorithms, which enforces proper operation of the cascade to maximize detection performance for a given energy budget. This is achieved by solving our proposed energy-constrained version of the Neyman-Pearson detection criterion, resulting in detector thresholds that can be updated to dynamically adjust to time-varying system resources and requirements. Sufficient conditions for a global solution for a cascade of an arbitrary number of detectors are given. Explicit solutions are derived for a two-stage cascade. Applied to a canonical detection problem, simulations show that our energy-aware cascaded detectors outperform an energy-aware detection algorithm based on incremental refinement, an existing alternate approach to developing energy-aware algorithms. Combining our framework with incremental refinement reveals a promising approach to developing energy-aware energy-efficient detection systems.","abstract_html":"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. The cascade architecture is known for being energy-efficient, but without proper operation can end up being energy-inefficient in practice. In this thesis, we propose a framework that imposes energy-awareness on cascaded detection algorithms, which enforces proper operation of the cascade to maximize detection performance for a given energy budget. This is achieved by solving our proposed energy-constrained version of the Neyman-Pearson detection criterion, resulting in detector thresholds that can be updated to dynamically adjust to time-varying system resources and requirements. Sufficient conditions for a global solution for a cascade of an arbitrary number of detectors are given. Explicit solutions are derived for a two-stage cascade. Applied to a canonical detection problem, simulations show that our energy-aware cascaded detectors outperform an energy-aware detection algorithm based on incremental refinement, an existing alternate approach to developing energy-aware algorithms. Combining our framework with incremental refinement reveals a promising approach to developing energy-aware energy-efficient detection systems.","abstract_has_math":false,"creators":["Jun, David M."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Jones, Douglas L."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-01-14T22:49:01Z","date_published":"2011-01-14T22:49:01Z","updated_at":"2026-07-22T22:25:11Z","subjects":["energy-aware","signal detection","incremental refinement","passive vigilance","scalable systems"],"languages":["en"],"rights":["Copyright 2010 David Moses Jun"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/18395","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Jones, Douglas L."]},{"key":"dc:creator","label":"Author","values":["Jun, David M."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-01-14T22:49:01Z","2010-12"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["energy-aware","signal detection","incremental refinement","passive vigilance","scalable systems"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2010 David Moses Jun"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/18395"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Low-power, scalable detection systems require aggressive techniques to achieve energy efficiency. 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