Tests For the Parameters of Chirp Signal Model
In this paper, the testing of the hypothesis problem on the unknown parameters involved in one-dimensional chirp signal model is explored. To be precise, we here theoretically investigate whether the vector of unknown parameters is the same as the vector with specified parameters. For that purpose,...
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| Veröffentlicht in: | IEEE transactions on signal processing 2019-08, Vol.67 (16), p.4291-4301 |
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| container_title | IEEE transactions on signal processing |
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| creator | Dhar, Subhra Sankar Kundu, Debasis Das, Ujjwal |
| description | In this paper, the testing of the hypothesis problem on the unknown parameters involved in one-dimensional chirp signal model is explored. To be precise, we here theoretically investigate whether the vector of unknown parameters is the same as the vector with specified parameters. For that purpose, we propose four tests based on the least squares and the least absolute deviation estimators of the unknown parameters using L_1 and L_2 distances. It is shown that the proposed tests are consistent (i.e., the power of the tests tend to one as the sample size tends to infinity). In addition, the asymptotic local power of the tests using contiguous (local) alternatives is also thoroughly studied. An extensive simulation study shows the satisfactory performance of the new tests, and the usefulness of the proposed tests is exhibited on a few benchmark real datasets that are closely associated with various chirp signal models. |
| doi_str_mv | 10.1109/TSP.2019.2928996 |
| format | Article |
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To be precise, we here theoretically investigate whether the vector of unknown parameters is the same as the vector with specified parameters. For that purpose, we propose four tests based on the least squares and the least absolute deviation estimators of the unknown parameters using <inline-formula><tex-math notation="LaTeX">L_1</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">L_2</tex-math></inline-formula> distances. It is shown that the proposed tests are consistent (i.e., the power of the tests tend to one as the sample size tends to infinity). In addition, the asymptotic local power of the tests using contiguous (local) alternatives is also thoroughly studied. An extensive simulation study shows the satisfactory performance of the new tests, and the usefulness of the proposed tests is exhibited on a few benchmark real datasets that are closely associated with various chirp signal models.]]></description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/TSP.2019.2928996</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Acoustics ; Birds ; Brain modeling ; Chirp ; chirp signal ; Chirp signals ; Computer simulation ; consistency of a test ; Estimating techniques ; Mathematical models ; Normal distribution ; Parameter estimation ; Radar ; Random variables ; Sonar ; Testing ; testing of hypothesis ; white noise</subject><ispartof>IEEE transactions on signal processing, 2019-08, Vol.67 (16), p.4291-4301</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-4091b2629155d62c6c610c14705040224c0d2c1e3dccf06afc374f51eeab63983</citedby><cites>FETCH-LOGICAL-c291t-4091b2629155d62c6c610c14705040224c0d2c1e3dccf06afc374f51eeab63983</cites><orcidid>0000-0001-9276-9068 ; 0000-0003-1355-3635 ; 0000-0002-9141-422X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8766871$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8766871$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Dhar, Subhra Sankar</creatorcontrib><creatorcontrib>Kundu, Debasis</creatorcontrib><creatorcontrib>Das, Ujjwal</creatorcontrib><title>Tests For the Parameters of Chirp Signal Model</title><title>IEEE transactions on signal processing</title><addtitle>TSP</addtitle><description><![CDATA[In this paper, the testing of the hypothesis problem on the unknown parameters involved in one-dimensional chirp signal model is explored. To be precise, we here theoretically investigate whether the vector of unknown parameters is the same as the vector with specified parameters. For that purpose, we propose four tests based on the least squares and the least absolute deviation estimators of the unknown parameters using <inline-formula><tex-math notation="LaTeX">L_1</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">L_2</tex-math></inline-formula> distances. It is shown that the proposed tests are consistent (i.e., the power of the tests tend to one as the sample size tends to infinity). In addition, the asymptotic local power of the tests using contiguous (local) alternatives is also thoroughly studied. An extensive simulation study shows the satisfactory performance of the new tests, and the usefulness of the proposed tests is exhibited on a few benchmark real datasets that are closely associated with various chirp signal models.]]></description><subject>Acoustics</subject><subject>Birds</subject><subject>Brain modeling</subject><subject>Chirp</subject><subject>chirp signal</subject><subject>Chirp signals</subject><subject>Computer simulation</subject><subject>consistency of a test</subject><subject>Estimating techniques</subject><subject>Mathematical models</subject><subject>Normal distribution</subject><subject>Parameter estimation</subject><subject>Radar</subject><subject>Random variables</subject><subject>Sonar</subject><subject>Testing</subject><subject>testing of hypothesis</subject><subject>white noise</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEFLAzEUhIMoWKt3wUvA867vJdns5ijFqlCx0AreQpp9a7e0bk22B_-9WVo8zRxmhuFj7BYhRwTzsFzMcwFocmFEZYw-YyM0CjNQpT5PHgqZFVX5ecmuYtwAoFJGj1i-pNhHPu0C79fE5y64HfUUIu8aPlm3Yc8X7de32_K3rqbtNbto3DbSzUnH7GP6tJy8ZLP359fJ4yzzwmCfKTC4Ejr5oqi18NprBI-qhAIUCKE81MIjydr7BrRrvCxVUyCRW2lpKjlm98fdfeh-Dumi3XSHkG5EK4SulExTQwqOKR-6GAM1dh_anQu_FsEOVGyiYgcq9kQlVe6OlZaI_uNVqXVVovwDnNJbKw</recordid><startdate>20190815</startdate><enddate>20190815</enddate><creator>Dhar, Subhra Sankar</creator><creator>Kundu, Debasis</creator><creator>Das, Ujjwal</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-9276-9068</orcidid><orcidid>https://orcid.org/0000-0003-1355-3635</orcidid><orcidid>https://orcid.org/0000-0002-9141-422X</orcidid></search><sort><creationdate>20190815</creationdate><title>Tests For the Parameters of Chirp Signal Model</title><author>Dhar, Subhra Sankar ; Kundu, Debasis ; Das, Ujjwal</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-4091b2629155d62c6c610c14705040224c0d2c1e3dccf06afc374f51eeab63983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Acoustics</topic><topic>Birds</topic><topic>Brain modeling</topic><topic>Chirp</topic><topic>chirp signal</topic><topic>Chirp signals</topic><topic>Computer simulation</topic><topic>consistency of a test</topic><topic>Estimating techniques</topic><topic>Mathematical models</topic><topic>Normal distribution</topic><topic>Parameter estimation</topic><topic>Radar</topic><topic>Random variables</topic><topic>Sonar</topic><topic>Testing</topic><topic>testing of hypothesis</topic><topic>white noise</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dhar, Subhra Sankar</creatorcontrib><creatorcontrib>Kundu, Debasis</creatorcontrib><creatorcontrib>Das, Ujjwal</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dhar, Subhra Sankar</au><au>Kundu, Debasis</au><au>Das, Ujjwal</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Tests For the Parameters of Chirp Signal Model</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>2019-08-15</date><risdate>2019</risdate><volume>67</volume><issue>16</issue><spage>4291</spage><epage>4301</epage><pages>4291-4301</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract><![CDATA[In this paper, the testing of the hypothesis problem on the unknown parameters involved in one-dimensional chirp signal model is explored. To be precise, we here theoretically investigate whether the vector of unknown parameters is the same as the vector with specified parameters. For that purpose, we propose four tests based on the least squares and the least absolute deviation estimators of the unknown parameters using <inline-formula><tex-math notation="LaTeX">L_1</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">L_2</tex-math></inline-formula> distances. It is shown that the proposed tests are consistent (i.e., the power of the tests tend to one as the sample size tends to infinity). In addition, the asymptotic local power of the tests using contiguous (local) alternatives is also thoroughly studied. An extensive simulation study shows the satisfactory performance of the new tests, and the usefulness of the proposed tests is exhibited on a few benchmark real datasets that are closely associated with various chirp signal models.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TSP.2019.2928996</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-9276-9068</orcidid><orcidid>https://orcid.org/0000-0003-1355-3635</orcidid><orcidid>https://orcid.org/0000-0002-9141-422X</orcidid></addata></record> |
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| source | IEEE Electronic Library (IEL) |
| subjects | Acoustics Birds Brain modeling Chirp chirp signal Chirp signals Computer simulation consistency of a test Estimating techniques Mathematical models Normal distribution Parameter estimation Radar Random variables Sonar Testing testing of hypothesis white noise |
| title | Tests For the Parameters of Chirp Signal Model |
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