Advance in the bat acoustic identification systems based on the audible spectrum using nonlinear dynamics characterization
•Combination of linear and non-linear parameterization.•As much as 12 chaos theory parameters are used.•Simple and quick method of classification.•Significant improvement of correct rate classification thanks chaos theory parameters. Frequential and time lineal parameters have shown a good performan...
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Veröffentlicht in: | Expert systems with applications 2015-12, Vol.42 (24), p.9528-9538 |
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creator | Alonso, Jesús B. Henríquez, Aarón Henríquez, Patricia Rodríguez-Herrera, Bernal Bolaños, Federico Alpízar, Priscilla Travieso, Carlos M. Cabrera, Josue |
description | •Combination of linear and non-linear parameterization.•As much as 12 chaos theory parameters are used.•Simple and quick method of classification.•Significant improvement of correct rate classification thanks chaos theory parameters.
Frequential and time lineal parameters have shown a good performance in the recognition of bat species and nowadays there are many works which obtain those characteristics very accurately. However, it is necessary to move forward and test the capabilities of other characterizations on bioacoustics successfully used in other fields. In this work the chaos theory, which is an area of nonlinear dynamics systems, is applied to bat acoustic identification. The database used in the evaluation consists of 50 bat calls of seven different classes extracted from a previous work. The combinations of linear and nonlinear parameters have resulted in an average error of 1.8%, improving the accuracy in 0.42%. The differences to identify between the most difficult species and the easiest ones have been reduced. |
doi_str_mv | 10.1016/j.eswa.2015.07.069 |
format | Article |
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Frequential and time lineal parameters have shown a good performance in the recognition of bat species and nowadays there are many works which obtain those characteristics very accurately. However, it is necessary to move forward and test the capabilities of other characterizations on bioacoustics successfully used in other fields. In this work the chaos theory, which is an area of nonlinear dynamics systems, is applied to bat acoustic identification. The database used in the evaluation consists of 50 bat calls of seven different classes extracted from a previous work. The combinations of linear and nonlinear parameters have resulted in an average error of 1.8%, improving the accuracy in 0.42%. The differences to identify between the most difficult species and the easiest ones have been reduced.</description><subject>Audio characterization</subject><subject>Bat identification</subject><subject>Bioacoustics</subject><subject>Dynamical systems</subject><subject>Errors</subject><subject>Expert systems</subject><subject>Nonlinear dynamics</subject><subject>Nonlinear parameterization</subject><subject>Nonlinearity</subject><subject>Recognition</subject><issn>0957-4174</issn><issn>1873-6793</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNp9kE1r3DAURUVJoZO0f6ArLbuxK8myZUE2IfQjEMgmXQtZem7eYMtTPTll8uvryXSd1d3cc-Eexj5LUUshu6_7Guivr5WQbS1MLTr7ju1kb5qqM7a5YDthW1NpafQHdkm0F0IaIcyOvdzEZ58CcEy8PAEffOE-LCsVDBwjpIIjBl9wSZyOVGCmrUMQ-XIG_BpxmIDTAULJ68xXwvSbpyVNmMBnHo_JzxiIhyeffSiQ8eV17yN7P_qJ4NP_vGK_vn97vP1Z3T_8uLu9ua-CFk2pBqn6TgRphgG01VbqNnjd2U6HZhyhawfTKxOjETI0YJUdew-6scorLa1RzRX7ct495OXPClTcjBRgmnyC7aiTvWp112rZbFV1roa8EGUY3SHj7PPRSeFOot3enUS7k2gnjNtEb9D1GYLtxDNCdhQQNqcR8-bExQXfwv8Bnf2JVQ</recordid><startdate>20151230</startdate><enddate>20151230</enddate><creator>Alonso, Jesús B.</creator><creator>Henríquez, Aarón</creator><creator>Henríquez, Patricia</creator><creator>Rodríguez-Herrera, Bernal</creator><creator>Bolaños, Federico</creator><creator>Alpízar, Priscilla</creator><creator>Travieso, Carlos M.</creator><creator>Cabrera, Josue</creator><general>Elsevier Ltd</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><orcidid>https://orcid.org/0000-0002-7866-585X</orcidid></search><sort><creationdate>20151230</creationdate><title>Advance in the bat acoustic identification systems based on the audible spectrum using nonlinear dynamics characterization</title><author>Alonso, Jesús B. ; Henríquez, Aarón ; Henríquez, Patricia ; Rodríguez-Herrera, Bernal ; Bolaños, Federico ; Alpízar, Priscilla ; Travieso, Carlos M. ; Cabrera, Josue</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c403t-b12860c17bbe4949145ca46964c3ffe65b7827dd701c3e929f8ae4392a2419723</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Audio characterization</topic><topic>Bat identification</topic><topic>Bioacoustics</topic><topic>Dynamical systems</topic><topic>Errors</topic><topic>Expert systems</topic><topic>Nonlinear dynamics</topic><topic>Nonlinear parameterization</topic><topic>Nonlinearity</topic><topic>Recognition</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Alonso, Jesús B.</creatorcontrib><creatorcontrib>Henríquez, Aarón</creatorcontrib><creatorcontrib>Henríquez, Patricia</creatorcontrib><creatorcontrib>Rodríguez-Herrera, Bernal</creatorcontrib><creatorcontrib>Bolaños, Federico</creatorcontrib><creatorcontrib>Alpízar, Priscilla</creatorcontrib><creatorcontrib>Travieso, Carlos M.</creatorcontrib><creatorcontrib>Cabrera, Josue</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>Expert systems with applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alonso, Jesús B.</au><au>Henríquez, Aarón</au><au>Henríquez, Patricia</au><au>Rodríguez-Herrera, Bernal</au><au>Bolaños, Federico</au><au>Alpízar, Priscilla</au><au>Travieso, Carlos M.</au><au>Cabrera, Josue</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Advance in the bat acoustic identification systems based on the audible spectrum using nonlinear dynamics characterization</atitle><jtitle>Expert systems with applications</jtitle><date>2015-12-30</date><risdate>2015</risdate><volume>42</volume><issue>24</issue><spage>9528</spage><epage>9538</epage><pages>9528-9538</pages><issn>0957-4174</issn><eissn>1873-6793</eissn><abstract>•Combination of linear and non-linear parameterization.•As much as 12 chaos theory parameters are used.•Simple and quick method of classification.•Significant improvement of correct rate classification thanks chaos theory parameters.
Frequential and time lineal parameters have shown a good performance in the recognition of bat species and nowadays there are many works which obtain those characteristics very accurately. However, it is necessary to move forward and test the capabilities of other characterizations on bioacoustics successfully used in other fields. In this work the chaos theory, which is an area of nonlinear dynamics systems, is applied to bat acoustic identification. The database used in the evaluation consists of 50 bat calls of seven different classes extracted from a previous work. The combinations of linear and nonlinear parameters have resulted in an average error of 1.8%, improving the accuracy in 0.42%. The differences to identify between the most difficult species and the easiest ones have been reduced.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.eswa.2015.07.069</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-7866-585X</orcidid></addata></record> |
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subjects | Audio characterization Bat identification Bioacoustics Dynamical systems Errors Expert systems Nonlinear dynamics Nonlinear parameterization Nonlinearity Recognition |
title | Advance in the bat acoustic identification systems based on the audible spectrum using nonlinear dynamics characterization |
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