{"id":{"repo_id":"unm","oai_identifier":"oai:digitalrepository.unm.edu:ece_etds-1123"},"canonical_url":"https://search.dev.ndltd.org/etd/unm/oai:digitalrepository.unm.edu:ece_etds-1123","repository":{"repo_id":"unm","name":"University of New Mexico","base_url":"https://digitalrepository.unm.edu/do/oai/"},"display":{"title":"Data compressive paradigm for spectral sensing and classification using electrically tunable detectors","abstract":"This dissertation contains three major parts: (1) demonstration of the algorithmic spectrometry in the mid-IR sensing regime using spectrally tunable quantum dots-in-a-well (DWELL) IR detector without employing any spectral filters; (2) further demonstration of the spectral-classification capability of tunable DWELL IR focal-plane array (FPA), again without using any spectral filters; and (3) development of a generalized filter-free data-compressive spectral sensing paradigm using the DWELL detector that enables arbitrarily specified MS sensing (e.g., spectral matched filtering, slope sensing, multicolor sensing, etc.) without using any spectral filters and possibly under constrained acquisition times.","abstract_html":"This dissertation contains three major parts: (1) demonstration of the algorithmic spectrometry in the mid-IR sensing regime using spectrally tunable quantum dots-in-a-well (DWELL) IR detector without employing any spectral filters; (2) further demonstration of the spectral-classification capability of tunable DWELL IR focal-plane array (FPA), again without using any spectral filters; and (3) development of a generalized filter-free data-compressive spectral sensing paradigm using the DWELL detector that enables arbitrarily specified MS sensing (e.g., spectral matched filtering, slope sensing, multicolor sensing, etc.) without using any spectral filters and possibly under constrained acquisition times.","abstract_has_math":false,"creators":["Jang, Woo-Yong"],"institution":null,"degree_name":"Computer Engineering","degree_level":"Dissertation","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":["Hayat, Majeed","Krishna, Sanjay","Brueck, Steven","Prasad, Sudhakar","Zarkesh-Ha, Payman"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-01-31T08:00:00Z","date_published":"2013-01-31T08:00:00Z","updated_at":"2026-07-24T05:27:19Z","subjects":["Infrared detectors.","Quantum wells.","Quantum dots.","Data compression (Computer science)"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalrepository.unm.edu/ece_etds/124","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hayat, Majeed","Krishna, Sanjay","Brueck, Steven","Prasad, Sudhakar","Zarkesh-Ha, Payman"]},{"key":"dc:creator","label":"Author","values":["Jang, Woo-Yong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation","Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Computer Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Infrared detectors.","Quantum wells.","Quantum dots.","Data compression (Computer science)"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalrepository.unm.edu/ece_etds/124"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This dissertation contains three major parts: (1) demonstration of the algorithmic spectrometry in the mid-IR sensing regime using spectrally tunable quantum dots-in-a-well (DWELL) IR detector without employing any spectral filters; (2) further demonstration of the spectral-classification capability of tunable DWELL IR focal-plane array (FPA), again without using any spectral filters; and (3) development of a generalized filter-free data-compressive spectral sensing paradigm using the DWELL detector that enables arbitrarily specified MS sensing (e.g., spectral matched filtering, slope sensing, multicolor sensing, etc.) without using any spectral filters and possibly under constrained acquisition times."]},{"key":"dc:title","label":"Title","values":["Data compressive paradigm for spectral sensing and classification using electrically tunable detectors"]}]}],"canonical_facts":{"dc:contributor":["Hayat, Majeed","Krishna, Sanjay","Brueck, Steven","Prasad, Sudhakar","Zarkesh-Ha, Payman"],"dc:creator":["Jang, Woo-Yong"],"dc:description.abstract":["This dissertation contains three major parts: (1) demonstration of the algorithmic spectrometry in the mid-IR sensing regime using spectrally tunable quantum dots-in-a-well (DWELL) IR detector without employing any spectral filters; 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