{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/41550"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/41550","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Signal reconstruction from discrete-time Wigner distribution","abstract":"Wigner distribution is considered to be one of the most powerful tools for time-frequency analysis of rumvstationary signals. Wigner distribution is a bilinear signal transformation which provides two dimensional time-frequency characterization of one dimensional signals. Although much work has been done recently in signal analysis and applications using Wigner distribution, not many synthesis methods for Wigner distribution have been reported in the literature. This thesis is concerned with signal synthesis from discrete-time Wigner distribution and from discrete-time pseudo-Wigner distribution and their applications in noise filtering and signal separation. Various algorithms are developed to reconstruct signals from the modified or specified Wigner distribution and pseudo-Wigner distribution which generally do not have a valid Wigner distributions or valid pseudo-Wigner distribution structures. These algorithms are successfully applied to the noise filtering and signal separation problems.","abstract_html":"Wigner distribution is considered to be one of the most powerful tools for time-frequency analysis of rumvstationary signals. Wigner distribution is a bilinear signal transformation which provides two dimensional time-frequency characterization of one dimensional signals. Although much work has been done recently in signal analysis and applications using Wigner distribution, not many synthesis methods for Wigner distribution have been reported in the literature. This thesis is concerned with signal synthesis from discrete-time Wigner distribution and from discrete-time pseudo-Wigner distribution and their applications in noise filtering and signal separation. Various algorithms are developed to reconstruct signals from the modified or specified Wigner distribution and pseudo-Wigner distribution which generally do not have a valid Wigner distributions or valid pseudo-Wigner distribution structures. These algorithms are successfully applied to the noise filtering and signal separation problems.","abstract_has_math":false,"creators":["Cheng, Siuling"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Electrical Engineering","degree_department":"Electrical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Yu, Kai Bor"],"committee_members":["deWolf, David A.","Ha, Tri Thuc"],"year":1985,"date_issued":"1985-03-18","date_published":"1985-03-18","updated_at":"2026-07-22T22:19:47Z","subjects":[],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-03122013-040100"],"render_values":[{"text":"etd-03122013-040100","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/41550","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Yu, Kai Bor"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["deWolf, David A.","Ha, Tri Thuc"]},{"key":"dc:contributor.department","label":"Department","values":["Electrical Engineering"]},{"key":"dc:creator","label":"Author","values":["Cheng, Siuling"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:31:32Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:31:32Z","2013-03-12"]},{"key":"dc:date.issued","label":"Date","values":["1985-03-18"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-03122013-040100"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/41550"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Wigner distribution is considered to be one of the most powerful tools for time-frequency analysis of rumvstationary signals. Wigner distribution is a bilinear signal transformation which provides two dimensional time-frequency characterization of one dimensional signals. Although much work has been done recently in signal analysis and applications using Wigner distribution, not many synthesis methods for Wigner distribution have been reported in the literature. This thesis is concerned with signal synthesis from discrete-time Wigner distribution and from discrete-time pseudo-Wigner distribution and their applications in noise filtering and signal separation. Various algorithms are developed to reconstruct signals from the modified or specified Wigner distribution and pseudo-Wigner distribution which generally do not have a valid Wigner distributions or valid pseudo-Wigner distribution structures. 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Wigner distribution is a bilinear signal transformation which provides two dimensional time-frequency characterization of one dimensional signals. Although much work has been done recently in signal analysis and applications using Wigner distribution, not many synthesis methods for Wigner distribution have been reported in the literature. This thesis is concerned with signal synthesis from discrete-time Wigner distribution and from discrete-time pseudo-Wigner distribution and their applications in noise filtering and signal separation. Various algorithms are developed to reconstruct signals from the modified or specified Wigner distribution and pseudo-Wigner distribution which generally do not have a valid Wigner distributions or valid pseudo-Wigner distribution structures. 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