{"id":{"repo_id":"nps","oai_identifier":"oai:calhoun.nps.edu:10945/20667"},"canonical_url":"https://search.dev.ndltd.org/etd/nps/oai:calhoun.nps.edu:10945/20667","repository":{"repo_id":"nps","name":"Naval Postgraduate School","base_url":"https://calhoun.nps.edu/server/oai/request"},"display":{"title":"Shift and scale invariant preprocessor.","abstract":"A preprocessor is designed to extract a set of features that enhance natural clustering by removing extraneous information. The design rerroves time shift and scale dependence by taking advantage of invariant properties of a Fourier transform followed by a Mellin transform. The preprocessor is realized using an FFT and a Mellin transform with a conventional error correction term. The error term proves to be indeterminate, but the error's bound is identified as the envelope for Mellin correction terms. Properties of the Mellin transform are employed to modify the signal so that the error correcting is no longer required. The resulting algorithms are tested with variously scaled inputs for which closed form solutions are known. With a verified modification in place, the preprocessor produces features that are invariant to shifting and scaling, while retaining enough information to classify canonic shapes, A method of improving performance is introduced.","abstract_html":"A preprocessor is designed to extract a set of features that enhance natural clustering by removing extraneous information. The design rerroves time shift and scale dependence by taking advantage of invariant properties of a Fourier transform followed by a Mellin transform. The preprocessor is realized using an FFT and a Mellin transform with a conventional error correction term. The error term proves to be indeterminate, but the error's bound is identified as the envelope for Mellin correction terms. Properties of the Mellin transform are employed to modify the signal so that the error correcting is no longer required. The resulting algorithms are tested with variously scaled inputs for which closed form solutions are known. With a verified modification in place, the preprocessor produces features that are invariant to shifting and scaling, while retaining enough information to classify canonic shapes, A method of improving performance is introduced.","abstract_has_math":false,"creators":["Huston, Norman E., Jr."],"institution":"Monterey, California. Naval Postgraduate School","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Electrical Engineering","school":null,"contributors":[],"advisors":["Wilson, L.A.","Hamming, Richard W."],"committee_chairs":[],"committee_members":[],"year":1981,"date_issued":"1981","date_published":"1981","updated_at":"2026-07-27T20:25:42Z","subjects":[],"languages":["en_US"],"rights":["This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. 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The design rerroves time shift and scale dependence by taking advantage of invariant properties of a Fourier transform followed by a Mellin transform. The preprocessor is realized using an FFT and a Mellin transform with a conventional error correction term. The error term proves to be indeterminate, but the error's bound is identified as the envelope for Mellin correction terms. Properties of the Mellin transform are employed to modify the signal so that the error correcting is no longer required. The resulting algorithms are tested with variously scaled inputs for which closed form solutions are known. With a verified modification in place, the preprocessor produces features that are invariant to shifting and scaling, while retaining enough information to classify canonic shapes, A method of improving performance is introduced."]},{"key":"dc:title","label":"Title","values":["Shift and scale invariant preprocessor."]}]}],"canonical_facts":{"dc:contributor.advisor":["Wilson, L.A.","Hamming, Richard W."],"dc:contributor.department":["Electrical Engineering"],"dc:creator":["Huston, Norman E., Jr."],"dc:date":["December 1981"],"dc:date.accessioned":["2012-11-20T00:17:21Z"],"dc:date.available":["2012-11-20T00:17:21Z"],"dc:date.issued":["1981"],"dc:description.abstract":["A preprocessor is designed to extract a set of features that enhance natural clustering by removing extraneous information. The design rerroves time shift and scale dependence by taking advantage of invariant properties of a Fourier transform followed by a Mellin transform. The preprocessor is realized using an FFT and a Mellin transform with a conventional error correction term. The error term proves to be indeterminate, but the error's bound is identified as the envelope for Mellin correction terms. Properties of the Mellin transform are employed to modify the signal so that the error correcting is no longer required. The resulting algorithms are tested with variously scaled inputs for which closed form solutions are known. With a verified modification in place, the preprocessor produces features that are invariant to shifting and scaling, while retaining enough information to classify canonic shapes, A method of improving performance is introduced."],"dc:identifier.uri":["https://hdl.handle.net/10945/20667"],"dc:language.iso":["en_US"],"dc:publisher":["Monterey, California. Naval Postgraduate School"],"dc:rights":["This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States."],"dc:title":["Shift and scale invariant preprocessor."],"dc:type":["Thesis"]},"updated_at":"2026-07-27T20:25:42Z"}