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New and used bills classification for cepstrum patterns
This paper proposes a new method to classify bills into different fatigue levels. Acoustic cepstrum patterns obtained from an acoustic signal generated by a bill passing through a banking machine are used for classification. The acoustic cepstrum patterns are fed to a competitive neural network with...
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| container_end_page | 3981 vol.6 |
| container_issue | |
| container_start_page | 3978 |
| container_title | |
| container_volume | 6 |
| creator | Teranishi, M. Omato, S. Kosaka, T. |
| description | This paper proposes a new method to classify bills into different fatigue levels. Acoustic cepstrum patterns obtained from an acoustic signal generated by a bill passing through a banking machine are used for classification. The acoustic cepstrum patterns are fed to a competitive neural network with the learning vector quantization (LVQ) algorithm, and classified the bill into three fatigue levels. The experimental results show that the proposed method is useful for classification of fatigue levels of bills, and the LVQ algorithm performs a good classification. |
| doi_str_mv | 10.1109/IJCNN.1999.830794 |
| format | conference_proceeding |
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Acoustic cepstrum patterns obtained from an acoustic signal generated by a bill passing through a banking machine are used for classification. The acoustic cepstrum patterns are fed to a competitive neural network with the learning vector quantization (LVQ) algorithm, and classified the bill into three fatigue levels. The experimental results show that the proposed method is useful for classification of fatigue levels of bills, and the LVQ algorithm performs a good classification.</description><identifier>ISSN: 1098-7576</identifier><identifier>ISBN: 0780355296</identifier><identifier>ISBN: 9780780355293</identifier><identifier>EISSN: 1558-3902</identifier><identifier>DOI: 10.1109/IJCNN.1999.830794</identifier><language>eng</language><publisher>IEEE</publisher><subject>Banking ; Cepstral analysis ; Cepstrum ; Educational institutions ; Electronic mail ; Fatigue ; Feature extraction ; Microphones ; Neural networks ; Signal generators</subject><ispartof>IJCNN'99. 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No.99CH36339)</title><addtitle>IJCNN</addtitle><description>This paper proposes a new method to classify bills into different fatigue levels. Acoustic cepstrum patterns obtained from an acoustic signal generated by a bill passing through a banking machine are used for classification. The acoustic cepstrum patterns are fed to a competitive neural network with the learning vector quantization (LVQ) algorithm, and classified the bill into three fatigue levels. The experimental results show that the proposed method is useful for classification of fatigue levels of bills, and the LVQ algorithm performs a good classification.</description><subject>Banking</subject><subject>Cepstral analysis</subject><subject>Cepstrum</subject><subject>Educational institutions</subject><subject>Electronic mail</subject><subject>Fatigue</subject><subject>Feature extraction</subject><subject>Microphones</subject><subject>Neural networks</subject><subject>Signal generators</subject><issn>1098-7576</issn><issn>1558-3902</issn><isbn>0780355296</isbn><isbn>9780780355293</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1999</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNp9zrsKwjAUgOHgBbw-gE55gdaTpml6ZlHUoZO7xDaFSFpLTkV8ewWdnf7hW37GVgJiIQA3x9O2KGKBiHEuQWM6YFOhVB5JhGTIZqBzkEolmI0-AJhHWulswmZEN4AMdIpTpgv75Kat-INsxa_Oe-KlN0SudqXp3b3l9T3w0nbUh0fDO9P3NrS0YOPaeLLLX-dsvd-dt4fIWWsvXXCNCa_L90v-xTfdpDi0</recordid><startdate>1999</startdate><enddate>1999</enddate><creator>Teranishi, M.</creator><creator>Omato, S.</creator><creator>Kosaka, T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>1999</creationdate><title>New and used bills classification for cepstrum patterns</title><author>Teranishi, M. ; Omato, S. ; Kosaka, T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_8307943</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Banking</topic><topic>Cepstral analysis</topic><topic>Cepstrum</topic><topic>Educational institutions</topic><topic>Electronic mail</topic><topic>Fatigue</topic><topic>Feature extraction</topic><topic>Microphones</topic><topic>Neural networks</topic><topic>Signal generators</topic><toplevel>online_resources</toplevel><creatorcontrib>Teranishi, M.</creatorcontrib><creatorcontrib>Omato, S.</creatorcontrib><creatorcontrib>Kosaka, T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Teranishi, M.</au><au>Omato, S.</au><au>Kosaka, T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>New and used bills classification for cepstrum patterns</atitle><btitle>IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)</btitle><stitle>IJCNN</stitle><date>1999</date><risdate>1999</risdate><volume>6</volume><spage>3978</spage><epage>3981 vol.6</epage><pages>3978-3981 vol.6</pages><issn>1098-7576</issn><eissn>1558-3902</eissn><isbn>0780355296</isbn><isbn>9780780355293</isbn><abstract>This paper proposes a new method to classify bills into different fatigue levels. Acoustic cepstrum patterns obtained from an acoustic signal generated by a bill passing through a banking machine are used for classification. The acoustic cepstrum patterns are fed to a competitive neural network with the learning vector quantization (LVQ) algorithm, and classified the bill into three fatigue levels. The experimental results show that the proposed method is useful for classification of fatigue levels of bills, and the LVQ algorithm performs a good classification.</abstract><pub>IEEE</pub><doi>10.1109/IJCNN.1999.830794</doi></addata></record> |
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| identifier | ISSN: 1098-7576 |
| ispartof | IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999, Vol.6, p.3978-3981 vol.6 |
| issn | 1098-7576 1558-3902 |
| language | eng |
| recordid | cdi_ieee_primary_830794 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Banking Cepstral analysis Cepstrum Educational institutions Electronic mail Fatigue Feature extraction Microphones Neural networks Signal generators |
| title | New and used bills classification for cepstrum patterns |
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