{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/43264"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/43264","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Analysis of parametric model signal processing techniques for signature analysis","abstract":"Five parametric modeling techniques have been identified to be possible alternatives to the Fast Fourier Transform (FFT) for signature analyses involving short data records. The developments in signal processing that have lead to these techniques are reviewed. Mathematical definitions for parametric models are provided in terms of time-domain stochastic difference equations as well as in terms of frequency-domain rational transfer functions. Computer programs are developed for implementation of each of the five parametric modeling techniques. Results are presented from studies conducted on simulated stochastic signals to characterize the performance of the parametric modeling techniques and to compare the performance of these techniques to the FFT. One of the parametric modeling techniques, Pisarenko Harmonic Decomposition shows outstanding performance in comparison to the FFT and to the other parametric modeling techniques.","abstract_html":"Five parametric modeling techniques have been identified to be possible alternatives to the Fast Fourier Transform (FFT) for signature analyses involving short data records. The developments in signal processing that have lead to these techniques are reviewed. Mathematical definitions for parametric models are provided in terms of time-domain stochastic difference equations as well as in terms of frequency-domain rational transfer functions. Computer programs are developed for implementation of each of the five parametric modeling techniques. Results are presented from studies conducted on simulated stochastic signals to characterize the performance of the parametric modeling techniques and to compare the performance of these techniques to the FFT. One of the parametric modeling techniques, Pisarenko Harmonic Decomposition shows outstanding performance in comparison to the FFT and to the other parametric modeling techniques.","abstract_has_math":false,"creators":["Patton, Kevin Bernard"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1988,"date_issued":"1988","date_published":"1988","updated_at":"2026-07-22T22:20:09Z","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-06122010-020424"],"render_values":[{"text":"etd-06122010-020424","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/43264","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Patton, Kevin Bernard"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:38:23Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:38:23Z","2010-06-12"]},{"key":"dc:date.issued","label":"Date","values":["1988"]},{"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":["Mechanical 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-06122010-020424"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/43264"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Five parametric modeling techniques have been identified to be possible alternatives to the Fast Fourier Transform (FFT) for signature analyses involving short data records. The developments in signal processing that have lead to these techniques are reviewed. Mathematical definitions for parametric models are provided in terms of time-domain stochastic difference equations as well as in terms of frequency-domain rational transfer functions. Computer programs are developed for implementation of each of the five parametric modeling techniques. Results are presented from studies conducted on simulated stochastic signals to characterize the performance of the parametric modeling techniques and to compare the performance of these techniques to the FFT. One of the parametric modeling techniques, Pisarenko Harmonic Decomposition shows outstanding performance in comparison to the FFT and to the other parametric modeling techniques."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["BTD"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Analysis of parametric model signal processing techniques for signature analysis"]}]}],"canonical_facts":{"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Patton, Kevin Bernard"],"dc:date.accessioned":["2014-03-14T21:38:23Z"],"dc:date.available":["2014-03-14T21:38:23Z","2010-06-12"],"dc:date.issued":["1988"],"dc:description.abstract":["Five parametric modeling techniques have been identified to be possible alternatives to the Fast Fourier Transform (FFT) for signature analyses involving short data records. The developments in signal processing that have lead to these techniques are reviewed. Mathematical definitions for parametric models are provided in terms of time-domain stochastic difference equations as well as in terms of frequency-domain rational transfer functions. Computer programs are developed for implementation of each of the five parametric modeling techniques. Results are presented from studies conducted on simulated stochastic signals to characterize the performance of the parametric modeling techniques and to compare the performance of these techniques to the FFT. One of the parametric modeling techniques, Pisarenko Harmonic Decomposition shows outstanding performance in comparison to the FFT and to the other parametric modeling techniques."],"dc:description.degree":["Master of Science"],"dc:format.medium":["BTD"],"dc:format.mimetype":["application/pdf"],"dc:identifier.other":["etd-06122010-020424"],"dc:identifier.uri":["http://hdl.handle.net/10919/43264"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["Analysis of parametric model signal processing techniques for signature analysis"],"dc:type":["Thesis"],"dc:type.dcmitype":["Text"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:20:09Z"}