A quantum classification algorithm for classification incomplete patterns based on entanglement measure
In this paper, a novel quantum classification algorithm that is based on competitive learning is presented to classify an input pattern that results from the failures of some sensors. As long as an incomplete pattern is presented to our model, the proposed algorithm performs the competitions between...
Gespeichert in:
| Veröffentlicht in: | Journal of intelligent & fuzzy systems 2020-01, Vol.38 (3), p.2809-2816 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 2816 |
|---|---|
| container_issue | 3 |
| container_start_page | 2809 |
| container_title | Journal of intelligent & fuzzy systems |
| container_volume | 38 |
| creator | Abdel-Aty, Abdel-Haleem Kadry, Heba Zidan, Mohammed Al-Sbou, Yazeed Zanaty, E. A. Abdel-Aty, Mahmoud |
| description | In this paper, a novel quantum classification algorithm that is based on competitive learning is presented to classify an input pattern that results from the failures of some sensors. As long as an incomplete pattern is presented to our model, the proposed algorithm performs the competitions between the neurons by applying some unitary transformations then measures the degree of entanglement using concurrence measure to find the winner class based on the winner-take-all technique. The proposed algorithm finds the most likely winning class label in between two binary competitive classes for an incomplete pattern presented to the proposed model. Because larger scale quantum computers are still in the lab, we studied the proposed algorithm on a case study. |
| doi_str_mv | 10.3233/JIFS-179566 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2371939895</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2371939895</sourcerecordid><originalsourceid>FETCH-LOGICAL-c369t-9151eb9a2604f9945981a3e0af5a4b1abe0a90f6f454d4e6b8c9a2169508b07a3</originalsourceid><addsrcrecordid>eNpdkE1LAzEURYMoWKsr_0DApYwmk4-ZLEuxtVJwoa7Dm2lSp8wk0ySz8N-bUleu3oF7uA8uQveUPLGSsee3zeqjoJUSUl6gGa0rUdRKVpeZieQFLbm8RjcxHgihlSjJDO0X-DiBS9OA2x5i7GzXQuq8w9DvfejS94CtD__DzrV-GHuTDB4hJRNcxA1Es8M5NC6B2_dmyIAHA3EK5hZdWeijufu7c_S1evlcvhbb9_VmudgWLZMqFYoKahoFpSTcKsWFqikwQ8AK4A2FJqMiVlou-I4b2dRtlqlUgtQNqYDN0cO5dwz-OJmY9MFPweWXumQVVUzVSmTr8Wy1wccYjNVj6AYIP5oSfVpSn5bU5yXZLyNOaAo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2371939895</pqid></control><display><type>article</type><title>A quantum classification algorithm for classification incomplete patterns based on entanglement measure</title><source>EBSCOhost Business Source Complete</source><creator>Abdel-Aty, Abdel-Haleem ; Kadry, Heba ; Zidan, Mohammed ; Al-Sbou, Yazeed ; Zanaty, E. A. ; Abdel-Aty, Mahmoud</creator><contributor>Farouk, Ahmed</contributor><creatorcontrib>Abdel-Aty, Abdel-Haleem ; Kadry, Heba ; Zidan, Mohammed ; Al-Sbou, Yazeed ; Zanaty, E. A. ; Abdel-Aty, Mahmoud ; Farouk, Ahmed</creatorcontrib><description>In this paper, a novel quantum classification algorithm that is based on competitive learning is presented to classify an input pattern that results from the failures of some sensors. As long as an incomplete pattern is presented to our model, the proposed algorithm performs the competitions between the neurons by applying some unitary transformations then measures the degree of entanglement using concurrence measure to find the winner class based on the winner-take-all technique. The proposed algorithm finds the most likely winning class label in between two binary competitive classes for an incomplete pattern presented to the proposed model. Because larger scale quantum computers are still in the lab, we studied the proposed algorithm on a case study.</description><identifier>ISSN: 1064-1246</identifier><identifier>EISSN: 1875-8967</identifier><identifier>DOI: 10.3233/JIFS-179566</identifier><language>eng</language><publisher>Amsterdam: IOS Press BV</publisher><subject>Algorithms ; Classification ; Computer simulation ; Machine learning ; Quantum computers ; Quantum entanglement</subject><ispartof>Journal of intelligent & fuzzy systems, 2020-01, Vol.38 (3), p.2809-2816</ispartof><rights>Copyright IOS Press BV 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c369t-9151eb9a2604f9945981a3e0af5a4b1abe0a90f6f454d4e6b8c9a2169508b07a3</citedby><cites>FETCH-LOGICAL-c369t-9151eb9a2604f9945981a3e0af5a4b1abe0a90f6f454d4e6b8c9a2169508b07a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><contributor>Farouk, Ahmed</contributor><creatorcontrib>Abdel-Aty, Abdel-Haleem</creatorcontrib><creatorcontrib>Kadry, Heba</creatorcontrib><creatorcontrib>Zidan, Mohammed</creatorcontrib><creatorcontrib>Al-Sbou, Yazeed</creatorcontrib><creatorcontrib>Zanaty, E. A.</creatorcontrib><creatorcontrib>Abdel-Aty, Mahmoud</creatorcontrib><title>A quantum classification algorithm for classification incomplete patterns based on entanglement measure</title><title>Journal of intelligent & fuzzy systems</title><description>In this paper, a novel quantum classification algorithm that is based on competitive learning is presented to classify an input pattern that results from the failures of some sensors. As long as an incomplete pattern is presented to our model, the proposed algorithm performs the competitions between the neurons by applying some unitary transformations then measures the degree of entanglement using concurrence measure to find the winner class based on the winner-take-all technique. The proposed algorithm finds the most likely winning class label in between two binary competitive classes for an incomplete pattern presented to the proposed model. Because larger scale quantum computers are still in the lab, we studied the proposed algorithm on a case study.</description><subject>Algorithms</subject><subject>Classification</subject><subject>Computer simulation</subject><subject>Machine learning</subject><subject>Quantum computers</subject><subject>Quantum entanglement</subject><issn>1064-1246</issn><issn>1875-8967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNpdkE1LAzEURYMoWKsr_0DApYwmk4-ZLEuxtVJwoa7Dm2lSp8wk0ySz8N-bUleu3oF7uA8uQveUPLGSsee3zeqjoJUSUl6gGa0rUdRKVpeZieQFLbm8RjcxHgihlSjJDO0X-DiBS9OA2x5i7GzXQuq8w9DvfejS94CtD__DzrV-GHuTDB4hJRNcxA1Es8M5NC6B2_dmyIAHA3EK5hZdWeijufu7c_S1evlcvhbb9_VmudgWLZMqFYoKahoFpSTcKsWFqikwQ8AK4A2FJqMiVlou-I4b2dRtlqlUgtQNqYDN0cO5dwz-OJmY9MFPweWXumQVVUzVSmTr8Wy1wccYjNVj6AYIP5oSfVpSn5bU5yXZLyNOaAo</recordid><startdate>20200101</startdate><enddate>20200101</enddate><creator>Abdel-Aty, Abdel-Haleem</creator><creator>Kadry, Heba</creator><creator>Zidan, Mohammed</creator><creator>Al-Sbou, Yazeed</creator><creator>Zanaty, E. A.</creator><creator>Abdel-Aty, Mahmoud</creator><general>IOS Press BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20200101</creationdate><title>A quantum classification algorithm for classification incomplete patterns based on entanglement measure</title><author>Abdel-Aty, Abdel-Haleem ; Kadry, Heba ; Zidan, Mohammed ; Al-Sbou, Yazeed ; Zanaty, E. A. ; Abdel-Aty, Mahmoud</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c369t-9151eb9a2604f9945981a3e0af5a4b1abe0a90f6f454d4e6b8c9a2169508b07a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Classification</topic><topic>Computer simulation</topic><topic>Machine learning</topic><topic>Quantum computers</topic><topic>Quantum entanglement</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Abdel-Aty, Abdel-Haleem</creatorcontrib><creatorcontrib>Kadry, Heba</creatorcontrib><creatorcontrib>Zidan, Mohammed</creatorcontrib><creatorcontrib>Al-Sbou, Yazeed</creatorcontrib><creatorcontrib>Zanaty, E. A.</creatorcontrib><creatorcontrib>Abdel-Aty, Mahmoud</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems 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>Journal of intelligent & fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Abdel-Aty, Abdel-Haleem</au><au>Kadry, Heba</au><au>Zidan, Mohammed</au><au>Al-Sbou, Yazeed</au><au>Zanaty, E. A.</au><au>Abdel-Aty, Mahmoud</au><au>Farouk, Ahmed</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A quantum classification algorithm for classification incomplete patterns based on entanglement measure</atitle><jtitle>Journal of intelligent & fuzzy systems</jtitle><date>2020-01-01</date><risdate>2020</risdate><volume>38</volume><issue>3</issue><spage>2809</spage><epage>2816</epage><pages>2809-2816</pages><issn>1064-1246</issn><eissn>1875-8967</eissn><abstract>In this paper, a novel quantum classification algorithm that is based on competitive learning is presented to classify an input pattern that results from the failures of some sensors. As long as an incomplete pattern is presented to our model, the proposed algorithm performs the competitions between the neurons by applying some unitary transformations then measures the degree of entanglement using concurrence measure to find the winner class based on the winner-take-all technique. The proposed algorithm finds the most likely winning class label in between two binary competitive classes for an incomplete pattern presented to the proposed model. Because larger scale quantum computers are still in the lab, we studied the proposed algorithm on a case study.</abstract><cop>Amsterdam</cop><pub>IOS Press BV</pub><doi>10.3233/JIFS-179566</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1064-1246 |
| ispartof | Journal of intelligent & fuzzy systems, 2020-01, Vol.38 (3), p.2809-2816 |
| issn | 1064-1246 1875-8967 |
| language | eng |
| recordid | cdi_proquest_journals_2371939895 |
| source | EBSCOhost Business Source Complete |
| subjects | Algorithms Classification Computer simulation Machine learning Quantum computers Quantum entanglement |
| title | A quantum classification algorithm for classification incomplete patterns based on entanglement measure |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T19%3A00%3A50IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20quantum%20classification%20algorithm%20for%20classification%20incomplete%20patterns%20based%20on%20entanglement%20measure&rft.jtitle=Journal%20of%20intelligent%20&%20fuzzy%20systems&rft.au=Abdel-Aty,%20Abdel-Haleem&rft.date=2020-01-01&rft.volume=38&rft.issue=3&rft.spage=2809&rft.epage=2816&rft.pages=2809-2816&rft.issn=1064-1246&rft.eissn=1875-8967&rft_id=info:doi/10.3233/JIFS-179566&rft_dat=%3Cproquest_cross%3E2371939895%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2371939895&rft_id=info:pmid/&rfr_iscdi=true |