{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/80762"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/80762","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Reliable and Low -Power Signal Processing via Algorithmic Noise -Tolerance","abstract":"In this dissertation, we address the problem of designing reliable and low-power VLSI systems for communications and DSP applications. An information theoretic framework to derive the lower bound on energy dissipation of VLSI circuits in presence of deep submicron noise is presented. It is shown that error-control coding can be employed to approach these bounds. We introduce algorithmic noise-tolerance (ANT) which is employing error-control at the algorithmic level to achieve reliable operation in presence of noise. We introduce voltage overscaling where the supply voltage is reduced beyond the limit imposed by the critical path delay to reduce energy dissipation. The resulting degradation in algorithmic performance is restored by employing ANT, thereby achieving energy savings while meeting the algorithmic performance specifications.","abstract_html":"In this dissertation, we address the problem of designing reliable and low-power VLSI systems for communications and DSP applications. An information theoretic framework to derive the lower bound on energy dissipation of VLSI circuits in presence of deep submicron noise is presented. It is shown that error-control coding can be employed to approach these bounds. We introduce algorithmic noise-tolerance (ANT) which is employing error-control at the algorithmic level to achieve reliable operation in presence of noise. We introduce voltage overscaling where the supply voltage is reduced beyond the limit imposed by the critical path delay to reduce energy dissipation. The resulting degradation in algorithmic performance is restored by employing ANT, thereby achieving energy savings while meeting the algorithmic performance specifications.","abstract_has_math":false,"creators":["Hegde, Rajamohana M."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":["Shanbhag, Naresh R."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T20:08:02Z","date_published":"2015-09-25T20:08:02Z","updated_at":"2026-07-22T22:26:14Z","subjects":["Engineering, Electronics and Electrical"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3044109"],"render_values":[{"text":"(MiAaPQ)AAI3044109","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/80762","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Shanbhag, Naresh R."]},{"key":"dc:creator","label":"Author","values":["Hegde, Rajamohana M."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T20:08:02Z","10000-01-01","2002"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"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":["Engineering, Electronics and Electrical"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/80762","(MiAaPQ)AAI3044109"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In this dissertation, we address the problem of designing reliable and low-power VLSI systems for communications and DSP applications. 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An information theoretic framework to derive the lower bound on energy dissipation of VLSI circuits in presence of deep submicron noise is presented. It is shown that error-control coding can be employed to approach these bounds. We introduce algorithmic noise-tolerance (ANT) which is employing error-control at the algorithmic level to achieve reliable operation in presence of noise. We introduce voltage overscaling where the supply voltage is reduced beyond the limit imposed by the critical path delay to reduce energy dissipation. The resulting degradation in algorithmic performance is restored by employing ANT, thereby achieving energy savings while meeting the algorithmic performance specifications.","Made available in DSpace on 2015-09-25T20:08:02Z (GMT). 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